---
DOAJ_listed: '1'
OA_place: publisher
OA_type: gold
_id: '18584'
abstract:
- lang: eng
text: In this paper, we describe the "Medium Bands, Mega Science" JWST Cycle 2 survey
(JWST-GO-4111) and demonstrate the power of these data to reveal both the spatially
integrated and spatially resolved properties of galaxies from the local Universe
to the era of cosmic dawn. Executed in 2023 November, MegaScience obtained ∼30
arcmin2 of deep multiband NIRCam imaging centered on the z ∼ 0.3 A2744 cluster,
including 11 medium-band filters and the two shortest-wavelength broadband filters,
F070W and F090W. Together, MegaScience and the UNCOVER Cycle 1 treasury program
provide a complete set of deep (∼28–30 magAB) images in all NIRCam medium- and
broadband filters. This unique data set allows us to precisely constrain photometric
redshifts, map stellar populations and dust attenuation for large samples of distant
galaxies, and examine the connection between galaxy structures and formation histories.
MegaScience also includes ∼17 arcmin2 of NIRISS parallel imaging in two broadband
and four medium-band filters from 0.9 to 4.8 μm, expanding the footprint where
robust spectral energy distribution (SED) fitting is possible. We provide example
SEDs and multiband cutouts at a variety of redshifts, and use a catalog of JWST
spectroscopic redshifts to show that MegaScience improves both the scatter and
catastrophic outlier rate of photometric redshifts by factors of 2–3. Additionally,
we demonstrate the spatially resolved science enabled by MegaScience by presenting
maps of the [O iii] line emission and continuum emission in three spectroscopically
confirmed z > 6 galaxies. We show that line emission in reionization-era galaxies
can be clumpy, extended, and spatially offset from continuum emission, implying
that galaxy assembly histories are complex even at these early epochs. We publicly
release fully reduced mosaics and photometric catalogs for both the NIRCam primary
and NIRISS parallel fields (jwst-uncover.github.io/megascience).
acknowledgement: "K.A.S. thanks Shelly Meyett, the MegaScience Program Coordinator,
for invaluable assistance designing WOPR 88967 and ensuring that this program was
fully observed. This proposal was conceived of and developed at the International
Space Science Institute (ISSI) in Bern, through ISSI International Team project
#562. This work is based on observations made with the NASA/ESA/CSA James Webb Space
Telescope. The raw data were obtained from the Mikulski Archive for Space Telescopes
at the Space Telescope Science Institute, which is operated by the Association of
Universities for Research in Astronomy, Inc., under NASA contract NAS 5-03127 for
JWST. These observations are associated with JWST Cycle 2 GO program #4111, and
this project has gratefully made use of a large number of public JWST programs in
the A2744 field including JWST-GO-2641, JWST-ERS-1324, JWST-DD-2756, JWST-GO-2883,
JWST-GO-3538, and JWST-GO-3516. Support for program JWST-GO-4111 was provided by
NASA through a grant from the Space Telescope Science Institute, which is operated
by the Associations of Universities for Research in Astronomy, Incorporated, under
NASA contract NAS5-26555.\r\n\r\nThe Cosmic Dawn Center is funded by the Danish
National Research Foundation (DNRF) under grant #140. P.D. acknowledges support
from the NWO grant 016.VIDI.189.162 (\"ODIN\") and warmly thanks the European Commission's
and University of Groningen's CO-FUND Rosalind Franklin program. This work has received
funding from the Swiss State Secretariat for Education, Research and Innovation
(SERI) under contract number MB22.00072, as well as from the Swiss National Science
Foundation (SNSF) through project grant 200020_207349. The work of C.C.W. is supported
by NOIRLab, which is managed by the Association of Universities for Research in
Astronomy (AURA) under a cooperative agreement with the National Science Foundation.
T.B.M. was supported by a CIERA Fellowship. H.A. is supported by CNES, focused on
the JWST mission, and by the Programme National Cosmology and Galaxies (PNCG) of
CNRS/INSU with INP and IN2P3, co-funded by CEA and CNES. The BGU lensing group acknowledges
support by grant No. 2020750 from the United States–Israel Binational Science Foundation
(BSF) and grant No. 2109066 from the United States National Science Foundation (NSF);
by the Ministry of Science & Technology, Israel; and by the Israel Science Foundation
grant No. 864/23. Y.F. acknowledges support from JSPS KAKENHI grant No. JP22K21349
and JP23K13149. R.P. and D.M. acknowledge funding from JWST-GO-02561.013 and JWST-GO-04111.035."
article_number: '101'
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Katherine A.
full_name: Suess, Katherine A.
last_name: Suess
- first_name: John R.
full_name: Weaver, John R.
last_name: Weaver
- first_name: Sedona H.
full_name: Price, Sedona H.
last_name: Price
- first_name: Richard
full_name: Pan, Richard
last_name: Pan
- first_name: Bingjie
full_name: Wang, Bingjie
last_name: Wang
- first_name: Rachel
full_name: Bezanson, Rachel
last_name: Bezanson
- first_name: Gabriel
full_name: Brammer, Gabriel
last_name: Brammer
- first_name: Sam E.
full_name: Cutler, Sam E.
last_name: Cutler
- first_name: Ivo
full_name: Labbé, Ivo
last_name: Labbé
- first_name: Joel
full_name: Leja, Joel
last_name: Leja
- first_name: Christina C.
full_name: Williams, Christina C.
last_name: Williams
- first_name: Katherine E.
full_name: Whitaker, Katherine E.
last_name: Whitaker
- first_name: Hakim
full_name: Atek, Hakim
last_name: Atek
- first_name: Pratika
full_name: Dayal, Pratika
last_name: Dayal
- first_name: Anna
full_name: De Graaff, Anna
last_name: De Graaff
- first_name: Robert
full_name: Feldmann, Robert
last_name: Feldmann
- first_name: Marijn
full_name: Franx, Marijn
last_name: Franx
- first_name: Yoshinobu
full_name: Fudamoto, Yoshinobu
last_name: Fudamoto
- first_name: Seiji
full_name: Fujimoto, Seiji
last_name: Fujimoto
- first_name: Lukas J.
full_name: Furtak, Lukas J.
last_name: Furtak
- first_name: Andy D.
full_name: Goulding, Andy D.
last_name: Goulding
- first_name: Jenny E.
full_name: Greene, Jenny E.
last_name: Greene
- first_name: Gourav
full_name: Khullar, Gourav
last_name: Khullar
- first_name: Vasily
full_name: Kokorev, Vasily
last_name: Kokorev
- first_name: Mariska
full_name: Kriek, Mariska
last_name: Kriek
- first_name: Brian
full_name: Lorenz, Brian
last_name: Lorenz
- first_name: Danilo
full_name: Marchesini, Danilo
last_name: Marchesini
- first_name: Michael V.
full_name: Maseda, Michael V.
last_name: Maseda
- first_name: Jorryt J
full_name: Matthee, Jorryt J
id: 7439a258-f3c0-11ec-9501-9df22fe06720
last_name: Matthee
orcid: 0000-0003-2871-127X
- first_name: Tim B.
full_name: Miller, Tim B.
last_name: Miller
- first_name: Ikki
full_name: Mitsuhashi, Ikki
last_name: Mitsuhashi
- first_name: Lamiya A.
full_name: Mowla, Lamiya A.
last_name: Mowla
- first_name: Adam
full_name: Muzzin, Adam
last_name: Muzzin
- first_name: Rohan P.
full_name: Naidu, Rohan P.
last_name: Naidu
- first_name: Themiya
full_name: Nanayakkara, Themiya
last_name: Nanayakkara
- first_name: Erica J.
full_name: Nelson, Erica J.
last_name: Nelson
- first_name: Pascal A.
full_name: Oesch, Pascal A.
last_name: Oesch
- first_name: David J.
full_name: Setton, David J.
last_name: Setton
- first_name: Heath
full_name: Shipley, Heath
last_name: Shipley
- first_name: Renske
full_name: Smit, Renske
last_name: Smit
- first_name: Justin S.
full_name: Spilker, Justin S.
last_name: Spilker
- first_name: Pieter
full_name: Van Dokkum, Pieter
last_name: Van Dokkum
- first_name: Adi
full_name: Zitrin, Adi
last_name: Zitrin
citation:
ama: 'Suess KA, Weaver JR, Price SH, et al. Medium bands, mega science: A JWST/NIRCam
medium-band imaging survey of A2744. Astrophysical Journal. 2024;976(1).
doi:10.3847/1538-4357/ad75fe'
apa: 'Suess, K. A., Weaver, J. R., Price, S. H., Pan, R., Wang, B., Bezanson, R.,
… Zitrin, A. (2024). Medium bands, mega science: A JWST/NIRCam medium-band imaging
survey of A2744. Astrophysical Journal. IOP Publishing. https://doi.org/10.3847/1538-4357/ad75fe'
chicago: 'Suess, Katherine A., John R. Weaver, Sedona H. Price, Richard Pan, Bingjie
Wang, Rachel Bezanson, Gabriel Brammer, et al. “Medium Bands, Mega Science: A
JWST/NIRCam Medium-Band Imaging Survey of A2744.” Astrophysical Journal.
IOP Publishing, 2024. https://doi.org/10.3847/1538-4357/ad75fe.'
ieee: 'K. A. Suess et al., “Medium bands, mega science: A JWST/NIRCam medium-band
imaging survey of A2744,” Astrophysical Journal, vol. 976, no. 1. IOP Publishing,
2024.'
ista: 'Suess KA, Weaver JR, Price SH, Pan R, Wang B, Bezanson R, Brammer G, Cutler
SE, Labbé I, Leja J, Williams CC, Whitaker KE, Atek H, Dayal P, De Graaff A, Feldmann
R, Franx M, Fudamoto Y, Fujimoto S, Furtak LJ, Goulding AD, Greene JE, Khullar
G, Kokorev V, Kriek M, Lorenz B, Marchesini D, Maseda MV, Matthee JJ, Miller TB,
Mitsuhashi I, Mowla LA, Muzzin A, Naidu RP, Nanayakkara T, Nelson EJ, Oesch PA,
Setton DJ, Shipley H, Smit R, Spilker JS, Van Dokkum P, Zitrin A. 2024. Medium
bands, mega science: A JWST/NIRCam medium-band imaging survey of A2744. Astrophysical
Journal. 976(1), 101.'
mla: 'Suess, Katherine A., et al. “Medium Bands, Mega Science: A JWST/NIRCam Medium-Band
Imaging Survey of A2744.” Astrophysical Journal, vol. 976, no. 1, 101,
IOP Publishing, 2024, doi:10.3847/1538-4357/ad75fe.'
short: K.A. Suess, J.R. Weaver, S.H. Price, R. Pan, B. Wang, R. Bezanson, G. Brammer,
S.E. Cutler, I. Labbé, J. Leja, C.C. Williams, K.E. Whitaker, H. Atek, P. Dayal,
A. De Graaff, R. Feldmann, M. Franx, Y. Fudamoto, S. Fujimoto, L.J. Furtak, A.D.
Goulding, J.E. Greene, G. Khullar, V. Kokorev, M. Kriek, B. Lorenz, D. Marchesini,
M.V. Maseda, J.J. Matthee, T.B. Miller, I. Mitsuhashi, L.A. Mowla, A. Muzzin,
R.P. Naidu, T. Nanayakkara, E.J. Nelson, P.A. Oesch, D.J. Setton, H. Shipley,
R. Smit, J.S. Spilker, P. Van Dokkum, A. Zitrin, Astrophysical Journal 976 (2024).
das_tickbox: '0'
date_created: 2024-11-24T23:01:48Z
date_published: 2024-11-14T00:00:00Z
date_updated: 2026-10-15T09:41:08Z
day: '14'
ddc:
- '520'
department:
- _id: JoMa
doi: 10.3847/1538-4357/ad75fe
external_id:
arxiv:
- '2404.13132'
isi:
- '001355710500001'
file:
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isi: 1
issue: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication: Astrophysical Journal
publication_identifier:
eissn:
- 1538-4357
issn:
- 0004-637X
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: yes
title: 'Medium bands, mega science: A JWST/NIRCam medium-band imaging survey of A2744'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 976
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '18996'
abstract:
- lang: eng
text: 'We consider the linear causal representation learning setting where we observe
a linear mixing of d unknown latent factors, which follow a linear structural
causal model. Recent work has shown that it is possible to recover the latent
factors as well as the underlying structural causal model over them, up to permutation
and scaling, provided that we have at least d environments, each of which corresponds
to perfect interventions on a single latent node (factor). After this powerful
result, a key open problem faced by the community has been to relax these conditions:
allow for coarser than perfect single-node interventions, and allow for fewer
than d of them, since the number of latent factors d could be very large. In this
work, we consider precisely such a setting, where we allow a smaller than d number
of environments, and also allow for very coarse interventions that can very coarsely
\textit{change the entire causal graph over the latent factors}. On the flip side,
we relax what we wish to extract to simply the \textit{list of nodes that have
shifted between one or more environments}. We provide a surprising identifiability
result that it is indeed possible, under some very mild standard assumptions,
to identify the set of shifted nodes. Our identifiability proof moreover is a
constructive one: we explicitly provide necessary and sufficient conditions for
a node to be a shifted node, and show that we can check these conditions given
observed data. Our algorithm lends itself very naturally to the sample setting
where instead of just interventional distributions, we are provided datasets of
samples from each of these distributions. We corroborate our results on both synthetic
experiments as well as an interesting psychometric dataset. The code can be found
at https://github.com/TianyuCodings/iLCS.'
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Tianyu
full_name: Chen, Tianyu
last_name: Chen
- first_name: Kevin
full_name: Bello, Kevin
last_name: Bello
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bryon
full_name: Aragam, Bryon
last_name: Aragam
- first_name: Pradeep Kumar
full_name: Ravikumar, Pradeep Kumar
last_name: Ravikumar
citation:
ama: 'Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. Identifying general
mechanism shifts in linear causal representations. In: 38th Conference on Neural
Information Processing Systems. Vol 37. Neural Information Processing Systems
Foundation; 2024. doi:10.52202/079017-1343'
apa: 'Chen, T., Bello, K., Locatello, F., Aragam, B., & Ravikumar, P. K. (2024).
Identifying general mechanism shifts in linear causal representations. In 38th
Conference on Neural Information Processing Systems (Vol. 37). Vancouver,
Canada: Neural Information Processing Systems Foundation. https://doi.org/10.52202/079017-1343'
chicago: Chen, Tianyu, Kevin Bello, Francesco Locatello, Bryon Aragam, and Pradeep
Kumar Ravikumar. “Identifying General Mechanism Shifts in Linear Causal Representations.”
In 38th Conference on Neural Information Processing Systems, Vol. 37. Neural
Information Processing Systems Foundation, 2024. https://doi.org/10.52202/079017-1343.
ieee: T. Chen, K. Bello, F. Locatello, B. Aragam, and P. K. Ravikumar, “Identifying
general mechanism shifts in linear causal representations,” in 38th Conference
on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.
ista: 'Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. 2024. Identifying general
mechanism shifts in linear causal representations. 38th Conference on Neural Information
Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in
Neural Information Processing Systems, vol. 37.'
mla: Chen, Tianyu, et al. “Identifying General Mechanism Shifts in Linear Causal
Representations.” 38th Conference on Neural Information Processing Systems,
vol. 37, Neural Information Processing Systems Foundation, 2024, doi:10.52202/079017-1343.
short: T. Chen, K. Bello, F. Locatello, B. Aragam, P.K. Ravikumar, in:, 38th Conference
on Neural Information Processing Systems, Neural Information Processing Systems
Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
das_tickbox: '0'
date_created: 2025-02-04T13:09:34Z
date_published: 2024-09-25T00:00:00Z
date_updated: 2026-10-15T09:44:18Z
day: '25'
ddc:
- '000'
department:
- _id: FrLo
doi: 10.52202/079017-1343
external_id:
arxiv:
- '2410.24059'
file:
- access_level: open_access
checksum: 75c3091e70bd2916cd94afbf40a0c425
content_type: application/pdf
creator: dernst
date_created: 2025-02-04T13:09:08Z
date_updated: 2025-02-04T13:09:08Z
file_id: '18997'
file_name: 2024_NeurIPS_Chen.pdf
file_size: 5659119
relation: main_file
success: 1
file_date_updated: 2025-02-04T13:09:08Z
fulldoi: https://doi.org/10.52202/079017-1343
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: 38th Conference on Neural Information Processing Systems
publication_identifier:
eissn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Identifying general mechanism shifts in linear causal representations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...
---
_id: '14451'
abstract:
- lang: eng
text: 'We investigate the potential of Multi-Objective, Deep Reinforcement Learning
for stock and cryptocurrency single-asset trading: in particular, we consider
a Multi-Objective algorithm which generalizes the reward functions and discount
factor (i.e., these components are not specified a priori, but incorporated in
the learning process). Firstly, using several important assets (BTCUSD, ETHUSDT,
XRPUSDT, AAPL, SPY, NIFTY50), we verify the reward generalization property of
the proposed Multi-Objective algorithm, and provide preliminary statistical evidence
showing increased predictive stability over the corresponding Single-Objective
strategy. Secondly, we show that the Multi-Objective algorithm has a clear edge
over the corresponding Single-Objective strategy when the reward mechanism is
sparse (i.e., when non-null feedback is infrequent over time). Finally, we discuss
the generalization properties with respect to the discount factor. The entirety
of our code is provided in open-source format.'
acknowledgement: Open access funding provided by Università degli Studi di Trieste
within the CRUI-CARE Agreement. Funding was provided by Austrian Science Fund (Grant
No. F65), Horizon 2020 (Grant No. 754411) and Österreichische Forschungsförderungsgesellschaft.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Federico
full_name: Cornalba, Federico
id: 2CEB641C-A400-11E9-A717-D712E6697425
last_name: Cornalba
orcid: 0000-0002-6269-5149
- first_name: Constantin
full_name: Disselkamp, Constantin
last_name: Disselkamp
- first_name: Davide
full_name: Scassola, Davide
last_name: Scassola
- first_name: Christopher
full_name: Helf, Christopher
last_name: Helf
citation:
ama: 'Cornalba F, Disselkamp C, Scassola D, Helf C. Multi-objective reward generalization:
Improving performance of Deep Reinforcement Learning for applications in single-asset
trading. Neural Computing and Applications. 2024;36(2):617-637. doi:10.1007/s00521-023-09033-7'
apa: 'Cornalba, F., Disselkamp, C., Scassola, D., & Helf, C. (2024). Multi-objective
reward generalization: Improving performance of Deep Reinforcement Learning for
applications in single-asset trading. Neural Computing and Applications.
Springer Nature. https://doi.org/10.1007/s00521-023-09033-7'
chicago: 'Cornalba, Federico, Constantin Disselkamp, Davide Scassola, and Christopher
Helf. “Multi-Objective Reward Generalization: Improving Performance of Deep Reinforcement
Learning for Applications in Single-Asset Trading.” Neural Computing and Applications.
Springer Nature, 2024. https://doi.org/10.1007/s00521-023-09033-7.'
ieee: 'F. Cornalba, C. Disselkamp, D. Scassola, and C. Helf, “Multi-objective reward
generalization: Improving performance of Deep Reinforcement Learning for applications
in single-asset trading,” Neural Computing and Applications, vol. 36, no.
2. Springer Nature, pp. 617–637, 2024.'
ista: 'Cornalba F, Disselkamp C, Scassola D, Helf C. 2024. Multi-objective reward
generalization: Improving performance of Deep Reinforcement Learning for applications
in single-asset trading. Neural Computing and Applications. 36(2), 617–637.'
mla: 'Cornalba, Federico, et al. “Multi-Objective Reward Generalization: Improving
Performance of Deep Reinforcement Learning for Applications in Single-Asset Trading.”
Neural Computing and Applications, vol. 36, no. 2, Springer Nature, 2024,
pp. 617–37, doi:10.1007/s00521-023-09033-7.'
short: F. Cornalba, C. Disselkamp, D. Scassola, C. Helf, Neural Computing and Applications
36 (2024) 617–637.
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: All datasets and the entire source code used in this paper
are available in open-source format at the repository https://github.com/trality/fire
. In particular, the instructions for reproducibility are contained in the README.md
file therein.
date_created: 2023-10-22T22:01:16Z
date_published: 2024-01-01T00:00:00Z
date_updated: 2026-10-15T09:42:15Z
day: '01'
ddc:
- '000'
department:
- _id: JuFi
doi: 10.1007/s00521-023-09033-7
ec_funded: 1
external_id:
arxiv:
- '2203.04579'
pmid:
- '38187995'
file:
- access_level: open_access
checksum: 04573d8e74c6119b97c2ca0a984e19a1
content_type: application/pdf
creator: dernst
date_created: 2024-07-16T08:08:54Z
date_updated: 2024-07-16T08:08:54Z
file_id: '17251'
file_name: 2024_NeuralCompApplications_Cornalba.pdf
file_size: 4412285
relation: main_file
success: 1
file_date_updated: 2024-07-16T08:08:54Z
fulldoi: https://doi.org/10.1007/s00521-023-09033-7
has_accepted_license: '1'
intvolume: ' 36'
issue: '2'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 617-637
pmid: 1
project:
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Neural Computing and Applications
publication_identifier:
eissn:
- 1433-3058
issn:
- 0941-0643
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: yes
scopus_import: '1'
status: public
supplementarymaterial: no
title: 'Multi-objective reward generalization: Improving performance of Deep Reinforcement
Learning for applications in single-asset trading'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 36
year: '2024'
...
---
_id: '17887'
abstract:
- lang: eng
text: We show convergence of the Navier-Stokes/Allen-Cahn system to a classical
sharp interface model for the two-phase flow of two viscous incompressible fluids
with same viscosities in a smooth bounded domain in two and three space dimensions
as long as a smooth solution of the limit system exists. Moreover, we obtain error
estimates with the aid of a relative entropy method. Our results hold provided
that the mobility mε>0 in the Allen-Cahn equation tends to zero in a subcritical
way, i.e., mε=m0εβ for some β∈(0,2) and m0>0 . The proof proceeds by showing
via a relative entropy argument that the solution to the Navier-Stokes/Allen-Cahn
system remains close to the solution of a perturbed version of the two-phase flow
problem, augmented by an extra mean curvature flow term mεHΓt in the interface
motion. In a second step, it is easy to see that the solution to the perturbed
problem is close to the original two-phase flow.
acknowledgement: "J. Fischer and M. Moser have received funding from the European
Research Council (ERC) under the European Union’s Horizon 2020 research and innovation
programme (grant agreement No 948819).\r\nOpen Access funding enabled and organized
by Projekt DEAL."
article_number: '77'
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Helmut
full_name: Abels, Helmut
last_name: Abels
- first_name: Julian L
full_name: Fischer, Julian L
id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87
last_name: Fischer
orcid: 0000-0002-0479-558X
- first_name: Maximilian
full_name: Moser, Maximilian
id: a60047a9-da77-11eb-85b4-c4dc385ebb8c
last_name: Moser
citation:
ama: Abels H, Fischer JL, Moser M. Approximation of classical two-phase flows of
viscous incompressible fluids by a Navier–Stokes/Allen–Cahn system. Archive
for Rational Mechanics and Analysis. 2024;248(5). doi:10.1007/s00205-024-02020-9
apa: Abels, H., Fischer, J. L., & Moser, M. (2024). Approximation of classical
two-phase flows of viscous incompressible fluids by a Navier–Stokes/Allen–Cahn
system. Archive for Rational Mechanics and Analysis. Springer Nature. https://doi.org/10.1007/s00205-024-02020-9
chicago: Abels, Helmut, Julian L Fischer, and Maximilian Moser. “Approximation of
Classical Two-Phase Flows of Viscous Incompressible Fluids by a Navier–Stokes/Allen–Cahn
System.” Archive for Rational Mechanics and Analysis. Springer Nature,
2024. https://doi.org/10.1007/s00205-024-02020-9.
ieee: H. Abels, J. L. Fischer, and M. Moser, “Approximation of classical two-phase
flows of viscous incompressible fluids by a Navier–Stokes/Allen–Cahn system,”
Archive for Rational Mechanics and Analysis, vol. 248, no. 5. Springer
Nature, 2024.
ista: Abels H, Fischer JL, Moser M. 2024. Approximation of classical two-phase flows
of viscous incompressible fluids by a Navier–Stokes/Allen–Cahn system. Archive
for Rational Mechanics and Analysis. 248(5), 77.
mla: Abels, Helmut, et al. “Approximation of Classical Two-Phase Flows of Viscous
Incompressible Fluids by a Navier–Stokes/Allen–Cahn System.” Archive for Rational
Mechanics and Analysis, vol. 248, no. 5, 77, Springer Nature, 2024, doi:10.1007/s00205-024-02020-9.
short: H. Abels, J.L. Fischer, M. Moser, Archive for Rational Mechanics and Analysis
248 (2024).
das_tickbox: '1'
dataavailabilitystatement: There is no associated data to the manuscript.
date_created: 2024-09-08T22:01:10Z
date_published: 2024-09-03T00:00:00Z
date_updated: 2026-10-15T09:44:17Z
day: '03'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s00205-024-02020-9
ec_funded: 1
external_id:
arxiv:
- '2311.02997'
isi:
- '001305530600001'
pmid:
- '39239088'
file:
- access_level: open_access
checksum: 98493a05b84e4513b6394dfad4851ddf
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creator: dernst
date_created: 2024-09-09T08:43:32Z
date_updated: 2024-09-09T08:43:32Z
file_id: '17938'
file_name: 2024_ArchiveRatAnalysis_Abels.pdf
file_size: 811131
relation: main_file
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file_date_updated: 2024-09-09T08:43:32Z
fulldoi: https://doi.org/10.1007/s00205-024-02020-9
has_accepted_license: '1'
intvolume: ' 248'
isi: 1
issue: '5'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Archive for Rational Mechanics and Analysis
publication_identifier:
eissn:
- 1432-0673
issn:
- 0003-9527
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: no
title: Approximation of classical two-phase flows of viscous incompressible fluids
by a Navier–Stokes/Allen–Cahn system
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 248
year: '2024'
...
---
_id: '12485'
abstract:
- lang: eng
text: In this paper we introduce the critical variational setting for parabolic
stochastic evolution equations of quasi- or semi-linear type. Our results improve
many of the abstract results in the classical variational setting. In particular,
we are able to replace the usual weak or local monotonicity condition by a more
flexible local Lipschitz condition. Moreover, the usual growth conditions on the
multiplicative noise are weakened considerably. Our new setting provides general
conditions under which local and global existence and uniqueness hold. Moreover,
we prove continuous dependence on the initial data. We show that many classical
SPDEs, which could not be covered by the classical variational setting, do fit
in the critical variational setting. In particular, this is the case for the Cahn-Hilliard
equations, tamed Navier-Stokes equations, and Allen-Cahn equation.
acknowledgement: The first author has received funding from the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 948819) . The second author is supported by the VICI subsidy
VI.C.212.027 of the Netherlands Organisation for Scientific Research (NWO).
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
- first_name: Mark
full_name: Veraar, Mark
last_name: Veraar
citation:
ama: Agresti A, Veraar M. The critical variational setting for stochastic evolution
equations. Probability Theory and Related Fields. 2024;188:957-1015. doi:10.1007/s00440-023-01249-x
apa: Agresti, A., & Veraar, M. (2024). The critical variational setting for
stochastic evolution equations. Probability Theory and Related Fields.
Springer Nature. https://doi.org/10.1007/s00440-023-01249-x
chicago: Agresti, Antonio, and Mark Veraar. “The Critical Variational Setting for
Stochastic Evolution Equations.” Probability Theory and Related Fields.
Springer Nature, 2024. https://doi.org/10.1007/s00440-023-01249-x.
ieee: A. Agresti and M. Veraar, “The critical variational setting for stochastic
evolution equations,” Probability Theory and Related Fields, vol. 188.
Springer Nature, pp. 957–1015, 2024.
ista: Agresti A, Veraar M. 2024. The critical variational setting for stochastic
evolution equations. Probability Theory and Related Fields. 188, 957–1015.
mla: Agresti, Antonio, and Mark Veraar. “The Critical Variational Setting for Stochastic
Evolution Equations.” Probability Theory and Related Fields, vol. 188,
Springer Nature, 2024, pp. 957–1015, doi:10.1007/s00440-023-01249-x.
short: A. Agresti, M. Veraar, Probability Theory and Related Fields 188 (2024) 957–1015.
das_tickbox: '1'
dataavailabilitystatement: Data sharing not applicable to this article as no datasets
were generated or analysed during the current study.
date_created: 2023-02-02T10:45:15Z
date_published: 2024-04-01T00:00:00Z
date_updated: 2026-10-15T09:45:31Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s00440-023-01249-x
ec_funded: 1
external_id:
arxiv:
- '2206.00230'
isi:
- '001154226500001'
file:
- access_level: open_access
checksum: b8572339dbc5b8de4934dc5fd34afc7d
content_type: application/pdf
creator: dernst
date_created: 2024-07-22T09:21:09Z
date_updated: 2024-07-22T09:21:09Z
file_id: '17296'
file_name: 2024_ProbTheory_Agresti.pdf
file_size: 942801
relation: main_file
success: 1
file_date_updated: 2024-07-22T09:21:09Z
fulldoi: https://doi.org/10.1007/s00440-023-01249-x
has_accepted_license: '1'
intvolume: ' 188'
isi: 1
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 957-1015
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Probability Theory and Related Fields
publication_identifier:
eissn:
- 1432-2064
issn:
- 0178-8051
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: no
title: The critical variational setting for stochastic evolution equations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 188
year: '2024'
...
---
_id: '12178'
abstract:
- lang: eng
text: In this paper we consider the stochastic primitive equation for geophysical
flows subject to transport noise and turbulent pressure. Admitting very rough
noise terms, the global existence and uniqueness of solutions to this stochastic
partial differential equation are proven using stochastic maximal L² regularity,
the theory of critical spaces for stochastic evolution equations, and global a
priori bounds. Compared to other results in this direction, we do not need any
smallness assumption on the transport noise which acts directly on the velocity
field and we also allow rougher noise terms. The adaptation to Stratonovich type
noise and, more generally, to variable viscosity and/or conductivity are discussed
as well.
acknowledgement: The authors thank the anonymous referees for their helpful comments
and suggestions. Open Access funding enabled and organized by Projekt DEAL.
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
- first_name: Matthias
full_name: Hieber, Matthias
last_name: Hieber
- first_name: Amru
full_name: Hussein, Amru
last_name: Hussein
- first_name: Martin
full_name: Saal, Martin
last_name: Saal
citation:
ama: 'Agresti A, Hieber M, Hussein A, Saal M. The stochastic primitive equations
with transport noise and turbulent pressure. Stochastics and Partial Differential
Equations: Analysis and Computations. 2024;12:53-133. doi:10.1007/s40072-022-00277-3'
apa: 'Agresti, A., Hieber, M., Hussein, A., & Saal, M. (2024). The stochastic
primitive equations with transport noise and turbulent pressure. Stochastics
and Partial Differential Equations: Analysis and Computations. Springer Nature.
https://doi.org/10.1007/s40072-022-00277-3'
chicago: 'Agresti, Antonio, Matthias Hieber, Amru Hussein, and Martin Saal. “The
Stochastic Primitive Equations with Transport Noise and Turbulent Pressure.” Stochastics
and Partial Differential Equations: Analysis and Computations. Springer Nature,
2024. https://doi.org/10.1007/s40072-022-00277-3.'
ieee: 'A. Agresti, M. Hieber, A. Hussein, and M. Saal, “The stochastic primitive
equations with transport noise and turbulent pressure,” Stochastics and Partial
Differential Equations: Analysis and Computations, vol. 12. Springer Nature,
pp. 53–133, 2024.'
ista: 'Agresti A, Hieber M, Hussein A, Saal M. 2024. The stochastic primitive equations
with transport noise and turbulent pressure. Stochastics and Partial Differential
Equations: Analysis and Computations. 12, 53–133.'
mla: 'Agresti, Antonio, et al. “The Stochastic Primitive Equations with Transport
Noise and Turbulent Pressure.” Stochastics and Partial Differential Equations:
Analysis and Computations, vol. 12, Springer Nature, 2024, pp. 53–133, doi:10.1007/s40072-022-00277-3.'
short: 'A. Agresti, M. Hieber, A. Hussein, M. Saal, Stochastics and Partial Differential
Equations: Analysis and Computations 12 (2024) 53–133.'
das_tickbox: '1'
dataavailabilitystatement: This manuscript has no associated data.
date_created: 2023-01-12T12:12:29Z
date_published: 2024-03-01T00:00:00Z
date_updated: 2026-10-15T09:44:54Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s40072-022-00277-3
external_id:
arxiv:
- '2109.09561'
isi:
- '000874389000001'
file:
- access_level: open_access
checksum: 59c9000761134d681bdf9d482664044c
content_type: application/pdf
creator: dernst
date_created: 2024-07-22T09:29:48Z
date_updated: 2024-07-22T09:29:48Z
file_id: '17297'
file_name: 2024_StochasticsEquations_Agresti.pdf
file_size: 1206413
relation: main_file
success: 1
file_date_updated: 2024-07-22T09:29:48Z
fulldoi: https://doi.org/10.1007/s40072-022-00277-3
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
keyword:
- Applied Mathematics
- Modeling and Simulation
- Statistics and Probability
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 53-133
publication: 'Stochastics and Partial Differential Equations: Analysis and Computations'
publication_identifier:
eissn:
- 2194-041X
issn:
- 2194-0401
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: yes
title: The stochastic primitive equations with transport noise and turbulent pressure
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 12
year: '2024'
...
---
_id: '17372'
abstract:
- lang: eng
text: 'In this paper, we investigate the global well-posedness of reaction-diffusion
systems with transport noise on the d-dimensional torus. We show new global well-posedness
results for a large class of scalar equations (e.g. the Allen-Cahn equation),
and dissipative systems (e.g. equations in coagulation dynamics). Moreover, we
prove global well-posedness for two weakly dissipative systems: Lotka-Volterra
equations for d∈{1,2,3,4} and the Brusselator for d∈{1,2,3}. Many of the results
are also new without transport noise. The proofs are based on maximal regularity
techniques, positivity results, and sharp blow-up criteria developed in our recent
works, combined with energy estimates based on Itô''s formula and stochastic Gronwall
inequalities. Key novelties include the introduction of new Lζ -coercivity/dissipativity
conditions and the development of an Lp(Lq) -framework for systems of reaction-diffusion
equations, which are needed when treating dimensions d∈{2,3} in the case of
cubic or higher order nonlinearities.'
acknowledgement: The first author’s research was supported by the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation programme
grant 948819. . The second author’s research was supported by the VICI subsidy VI.C.212.027
of the Netherlands Organisation for Scientific Research (NWO).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
- first_name: Mark
full_name: Veraar, Mark
last_name: Veraar
citation:
ama: 'Agresti A, Veraar M. Reaction-diffusion equations with transport noise and
critical superlinear diffusion: Global well-posedness of weakly dissipative systems.
SIAM Journal on Mathematical Analysis. 2024;56(4):4870-4927. doi:10.1137/23M1562482'
apa: 'Agresti, A., & Veraar, M. (2024). Reaction-diffusion equations with transport
noise and critical superlinear diffusion: Global well-posedness of weakly dissipative
systems. SIAM Journal on Mathematical Analysis. Society for Industrial
and Applied Mathematics. https://doi.org/10.1137/23M1562482'
chicago: 'Agresti, Antonio, and Mark Veraar. “Reaction-Diffusion Equations with
Transport Noise and Critical Superlinear Diffusion: Global Well-Posedness of Weakly
Dissipative Systems.” SIAM Journal on Mathematical Analysis. Society for
Industrial and Applied Mathematics, 2024. https://doi.org/10.1137/23M1562482.'
ieee: 'A. Agresti and M. Veraar, “Reaction-diffusion equations with transport noise
and critical superlinear diffusion: Global well-posedness of weakly dissipative
systems,” SIAM Journal on Mathematical Analysis, vol. 56, no. 4. Society
for Industrial and Applied Mathematics, pp. 4870–4927, 2024.'
ista: 'Agresti A, Veraar M. 2024. Reaction-diffusion equations with transport noise
and critical superlinear diffusion: Global well-posedness of weakly dissipative
systems. SIAM Journal on Mathematical Analysis. 56(4), 4870–4927.'
mla: 'Agresti, Antonio, and Mark Veraar. “Reaction-Diffusion Equations with Transport
Noise and Critical Superlinear Diffusion: Global Well-Posedness of Weakly Dissipative
Systems.” SIAM Journal on Mathematical Analysis, vol. 56, no. 4, Society
for Industrial and Applied Mathematics, 2024, pp. 4870–927, doi:10.1137/23M1562482.'
short: A. Agresti, M. Veraar, SIAM Journal on Mathematical Analysis 56 (2024) 4870–4927.
corr_author: '1'
das_tickbox: '0'
date_created: 2024-08-04T22:01:21Z
date_published: 2024-08-01T00:00:00Z
date_updated: 2026-10-15T09:43:41Z
day: '01'
department:
- _id: JuFi
doi: 10.1137/23M1562482
ec_funded: 1
external_id:
arxiv:
- '2301.06897'
isi:
- '001315424500021'
fulldoi: https://doi.org/10.1137/23M1562482
intvolume: ' 56'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2301.06897
month: '08'
oa: 1
oa_version: Preprint
page: 4870-4927
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: SIAM Journal on Mathematical Analysis
publication_identifier:
eissn:
- 1095-7154
issn:
- 0036-1410
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: 'Reaction-diffusion equations with transport noise and critical superlinear
diffusion: Global well-posedness of weakly dissipative systems'
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 56
year: '2024'
...
---
_id: '14884'
abstract:
- lang: eng
text: We perform a stochastic homogenization analysis for composite materials exhibiting
a random microstructure. Under the assumptions of stationarity and ergodicity,
we characterize the Gamma-limit of a micromagnetic energy functional defined on
magnetizations taking value in the unit sphere and including both symmetric and
antisymmetric exchange contributions. This Gamma-limit corresponds to a micromagnetic
energy functional with homogeneous coefficients. We provide explicit formulas
for the effective magnetic properties of the composite material in terms of homogenization
correctors. Additionally, the variational analysis of the two exchange energy
terms is performed in the more general setting of functionals defined on manifold-valued
maps with Sobolev regularity, in the case in which the target manifold is a bounded,
orientable smooth surface with tubular neighborhood of uniform thickness. Eventually,
we present an explicit characterization of minimizers of the effective exchange
in the case of magnetic multilayers, providing quantitative evidence of Dzyaloshinskii’s
predictions on the emergence of helical structures in composite ferromagnetic
materials with stochastic microstructure.
acknowledgement: All authors acknowledge support of the Austrian Science Fund (FWF)
through the SFB project F65. The research of E. Davoli and L. D’Elia has additionally
been supported by the FWF through grants V662, Y1292, and P35359, as well as from
OeAD through the WTZ grant CZ09/2023.
article_number: '30'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Elisa
full_name: Davoli, Elisa
last_name: Davoli
- first_name: Lorenza
full_name: D’Elia, Lorenza
last_name: D’Elia
- first_name: Jonas
full_name: Ingmanns, Jonas
id: 71523d30-15b2-11ec-abd3-f80aa909d6b0
last_name: Ingmanns
orcid: 0009-0008-1310-7946
citation:
ama: Davoli E, D’Elia L, Ingmanns J. Stochastic homogenization of micromagnetic
energies and emergence of magnetic skyrmions. Journal of Nonlinear Science.
2024;34(2). doi:10.1007/s00332-023-10005-3
apa: Davoli, E., D’Elia, L., & Ingmanns, J. (2024). Stochastic homogenization
of micromagnetic energies and emergence of magnetic skyrmions. Journal of Nonlinear
Science. Springer Nature. https://doi.org/10.1007/s00332-023-10005-3
chicago: Davoli, Elisa, Lorenza D’Elia, and Jonas Ingmanns. “Stochastic Homogenization
of Micromagnetic Energies and Emergence of Magnetic Skyrmions.” Journal of
Nonlinear Science. Springer Nature, 2024. https://doi.org/10.1007/s00332-023-10005-3.
ieee: E. Davoli, L. D’Elia, and J. Ingmanns, “Stochastic homogenization of micromagnetic
energies and emergence of magnetic skyrmions,” Journal of Nonlinear Science,
vol. 34, no. 2. Springer Nature, 2024.
ista: Davoli E, D’Elia L, Ingmanns J. 2024. Stochastic homogenization of micromagnetic
energies and emergence of magnetic skyrmions. Journal of Nonlinear Science. 34(2),
30.
mla: Davoli, Elisa, et al. “Stochastic Homogenization of Micromagnetic Energies
and Emergence of Magnetic Skyrmions.” Journal of Nonlinear Science, vol.
34, no. 2, 30, Springer Nature, 2024, doi:10.1007/s00332-023-10005-3.
short: E. Davoli, L. D’Elia, J. Ingmanns, Journal of Nonlinear Science 34 (2024).
das_tickbox: '1'
dataavailabilitystatement: Data sharing is not applicable to this article as no datasets
were generated or analyzed during the current study.
date_created: 2024-01-28T23:01:42Z
date_published: 2024-01-23T00:00:00Z
date_updated: 2026-10-15T09:46:00Z
day: '23'
department:
- _id: JuFi
doi: 10.1007/s00332-023-10005-3
external_id:
arxiv:
- '2306.05151'
isi:
- '001147480200001'
fulldoi: https://doi.org/10.1007/s00332-023-10005-3
intvolume: ' 34'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2306.05151
month: '01'
oa: 1
oa_version: Preprint
project:
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
publication: Journal of Nonlinear Science
publication_identifier:
eissn:
- 1432-1467
issn:
- 0938-8974
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: no
title: Stochastic homogenization of micromagnetic energies and emergence of magnetic
skyrmions
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 34
year: '2024'
...
---
OA_place: publisher
OA_type: free access
_id: '19005'
abstract:
- lang: eng
text: "Causal representation learning promises to extend causal models to hidden
causal\r\nvariables from raw entangled measurements. However, most progress has
focused\r\non proving identifiability results in different settings, and we are
not aware of any\r\nsuccessful real-world application. At the same time, the field
of dynamical systems\r\nbenefited from deep learning and scaled to countless applications
but does not allow\r\nparameter identification. In this paper, we draw a clear
connection between the two\r\nand their key assumptions, allowing us to apply
identifiable methods developed\r\nin causal representation learning to dynamical
systems. At the same time, we can\r\nleverage scalable differentiable solvers
developed for differential equations to build\r\nmodels that are both identifiable
and practical. Overall, we learn explicitly controllable models that isolate the
trajectory-specific parameters for further downstream\r\ntasks such as out-of-distribution
classification or treatment effect estimation. We\r\nexperiment with a wind simulator
with partially known factors of variation. We\r\nalso apply the resulting model
to real-world climate data and successfully answer\r\ndownstream causal questions
in line with existing literature on climate change.\r\nCode is available at https://github.com/CausalLearningAI/crl-dynamical-systems."
acknowledgement: "We thank Niklas Boers for recommending the SpeedyWeather simulator
and Valentino Maiorca\r\nfor guidance on Fourier transformation for SST data. We
are also grateful to Shimeng Huang and Riccardo Cadei for their feedback on the
treatment effect estimation experiment and to Jiale Chen and Adeel Pervez for their
assistance with the solver implementation. Finally, we appreciate the anonymous
reviewers for their insightful suggestions, which helped improve the manuscript. "
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Dingling
full_name: Yao, Dingling
id: d3e02e50-48a8-11ee-8f62-c108061797fa
last_name: Yao
- first_name: Caroline J
full_name: Muller, Caroline J
id: f978ccb0-3f7f-11eb-b193-b0e2bd13182b
last_name: Muller
orcid: 0000-0001-5836-5350
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Yao D, Muller CJ, Locatello F. Marrying causal representation learning with
dynamical systems for science. In: 38th Conference on Neural Information Processing
Systems. Vol 37. Neural Information Processing Systems Foundation; 2024. doi:10.52202/079017-2290'
apa: 'Yao, D., Muller, C. J., & Locatello, F. (2024). Marrying causal representation
learning with dynamical systems for science. In 38th Conference on Neural Information
Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing
Systems Foundation. https://doi.org/10.52202/079017-2290'
chicago: Yao, Dingling, Caroline J Muller, and Francesco Locatello. “Marrying Causal
Representation Learning with Dynamical Systems for Science.” In 38th Conference
on Neural Information Processing Systems, Vol. 37. Neural Information Processing
Systems Foundation, 2024. https://doi.org/10.52202/079017-2290.
ieee: D. Yao, C. J. Muller, and F. Locatello, “Marrying causal representation learning
with dynamical systems for science,” in 38th Conference on Neural Information
Processing Systems, Vancouver, Canada, 2024, vol. 37.
ista: 'Yao D, Muller CJ, Locatello F. 2024. Marrying causal representation learning
with dynamical systems for science. 38th Conference on Neural Information Processing
Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information
Processing Systems, vol. 37.'
mla: Yao, Dingling, et al. “Marrying Causal Representation Learning with Dynamical
Systems for Science.” 38th Conference on Neural Information Processing Systems,
vol. 37, Neural Information Processing Systems Foundation, 2024, doi:10.52202/079017-2290.
short: D. Yao, C.J. Muller, F. Locatello, in:, 38th Conference on Neural Information
Processing Systems, Neural Information Processing Systems Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
corr_author: '1'
das_tickbox: '0'
date_created: 2025-02-05T07:49:00Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2026-10-15T09:47:17Z
day: '01'
ddc:
- '000'
- '550'
department:
- _id: CaMu
- _id: FrLo
doi: 10.52202/079017-2290
external_id:
arxiv:
- '2405.13888'
file:
- access_level: open_access
checksum: fe8832367e7143876f178244385d859e
content_type: application/pdf
creator: dernst
date_created: 2025-02-05T07:44:58Z
date_updated: 2025-02-05T07:44:58Z
file_id: '19006'
file_name: 2024_NeurIPS_Yao.pdf
file_size: 2595855
relation: main_file
success: 1
file_date_updated: 2025-02-05T07:44:58Z
fulldoi: https://doi.org/10.52202/079017-2290
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: 38th Conference on Neural Information Processing Systems
publication_identifier:
eissn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/CausalLearningAI/crl-dynamical-systems
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Marrying causal representation learning with dynamical systems for science
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '13129'
abstract:
- lang: eng
text: "We study the representative volume element (RVE) method, which is a method
to approximately infer the effective behavior ahom of a stationary random medium.
The latter is described by a coefficient field a(x) generated from a given ensemble
⟨⋅⟩ and the corresponding linear elliptic operator −∇⋅a∇. In line with the theory
of homogenization, the method proceeds by computing d=3 correctors (d denoting
the space dimension). To be numerically tractable, this computation has to be
done on a finite domain: the so-called representative volume element, i.e., a
large box with, say, periodic boundary conditions. The main message of this article
is: Periodize the ensemble instead of its realizations. By this, we mean that
it is better to sample from a suitably periodized ensemble than to periodically
extend the restriction of a realization a(x) from the whole-space ensemble ⟨⋅⟩.
We make this point by investigating the bias (or systematic error), i.e., the
difference between ahom and the expected value of the RVE method, in terms of
its scaling w.r.t. the lateral size L of the box. In case of periodizing a(x),
we heuristically argue that this error is generically O(L−1). In case of a suitable
periodization of ⟨⋅⟩\r\n, we rigorously show that it is O(L−d). In fact, we give
a characterization of the leading-order error term for both strategies and argue
that even in the isotropic case it is generically non-degenerate. We carry out
the rigorous analysis in the convenient setting of ensembles ⟨⋅⟩\r\n of Gaussian
type, which allow for a straightforward periodization, passing via the (integrable)
covariance function. This setting has also the advantage of making the Price theorem
and the Malliavin calculus available for optimal stochastic estimates of correctors.
We actually need control of second-order correctors to capture the leading-order
error term. This is due to inversion symmetry when applying the two-scale expansion
to the Green function. As a bonus, we present a stream-lined strategy to estimate
the error in a higher-order two-scale expansion of the Green function."
acknowledgement: Open access funding provided by Institute of Science and Technology
(IST Austria).
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Nicolas
full_name: Clozeau, Nicolas
id: fea1b376-906f-11eb-847d-b2c0cf46455b
last_name: Clozeau
- first_name: Marc
full_name: Josien, Marc
last_name: Josien
- first_name: Felix
full_name: Otto, Felix
last_name: Otto
- first_name: Qiang
full_name: Xu, Qiang
last_name: Xu
citation:
ama: 'Clozeau N, Josien M, Otto F, Xu Q. Bias in the representative volume element
method: Periodize the ensemble instead of its realizations. Foundations of
Computational Mathematics. 2024;24:1305-1387. doi:10.1007/s10208-023-09613-y'
apa: 'Clozeau, N., Josien, M., Otto, F., & Xu, Q. (2024). Bias in the representative
volume element method: Periodize the ensemble instead of its realizations. Foundations
of Computational Mathematics. Springer Nature. https://doi.org/10.1007/s10208-023-09613-y'
chicago: 'Clozeau, Nicolas, Marc Josien, Felix Otto, and Qiang Xu. “Bias in the
Representative Volume Element Method: Periodize the Ensemble Instead of Its Realizations.”
Foundations of Computational Mathematics. Springer Nature, 2024. https://doi.org/10.1007/s10208-023-09613-y.'
ieee: 'N. Clozeau, M. Josien, F. Otto, and Q. Xu, “Bias in the representative volume
element method: Periodize the ensemble instead of its realizations,” Foundations
of Computational Mathematics, vol. 24. Springer Nature, pp. 1305–1387, 2024.'
ista: 'Clozeau N, Josien M, Otto F, Xu Q. 2024. Bias in the representative volume
element method: Periodize the ensemble instead of its realizations. Foundations
of Computational Mathematics. 24, 1305–1387.'
mla: 'Clozeau, Nicolas, et al. “Bias in the Representative Volume Element Method:
Periodize the Ensemble Instead of Its Realizations.” Foundations of Computational
Mathematics, vol. 24, Springer Nature, 2024, pp. 1305–87, doi:10.1007/s10208-023-09613-y.'
short: N. Clozeau, M. Josien, F. Otto, Q. Xu, Foundations of Computational Mathematics
24 (2024) 1305–1387.
corr_author: '1'
das_tickbox: '0'
date_created: 2023-06-11T22:00:40Z
date_published: 2024-08-01T00:00:00Z
date_updated: 2026-10-15T09:47:37Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s10208-023-09613-y
external_id:
isi:
- '000999623100001'
file:
- access_level: open_access
checksum: ec0582e2b55e2703a7da2686ae0d682e
content_type: application/pdf
creator: dernst
date_created: 2025-01-09T07:36:57Z
date_updated: 2025-01-09T07:36:57Z
file_id: '18782'
file_name: 2024_FoundCompMath_Clozeau.pdf
file_size: 1454406
relation: main_file
success: 1
file_date_updated: 2025-01-09T07:36:57Z
fulldoi: https://doi.org/10.1007/s10208-023-09613-y
has_accepted_license: '1'
intvolume: ' 24'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 1305-1387
publication: Foundations of Computational Mathematics
publication_identifier:
eissn:
- 1615-3383
issn:
- 1615-3375
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: yes
title: 'Bias in the representative volume element method: Periodize the ensemble instead
of its realizations'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 24
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '12486'
abstract:
- lang: eng
text: This paper is concerned with the problem of regularization by noise of systems
of reaction–diffusion equations with mass control. It is known that strong solutions
to such systems of PDEs may blow-up in finite time. Moreover, for many systems
of practical interest, establishing whether the blow-up occurs or not is an open
question. Here we prove that a suitable multiplicative noise of transport type
has a regularizing effect. More precisely, for both a sufficiently noise intensity
and a high spectrum, the blow-up of strong solutions is delayed up to an arbitrary
large time. Global existence is shown for the case of exponentially decreasing
mass. The proofs combine and extend recent developments in regularization by noise
and in the Lp(Lq)-approach to stochastic PDEs, highlighting new connections between
the two areas.
acknowledgement: "The author has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(Grant Agreement No. 948819).\r\nThe author thanks Lorenzo Dello Schiavo, Lucio
Galeati and Mark Veraar for helpful comments. The author acknowledges Caterina Balzotti
for her support in creating the picture. The author\r\nthanks the anonymous referee
for helpful comments. "
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
citation:
ama: 'Agresti A. Delayed blow-up and enhanced diffusion by transport noise for systems
of reaction-diffusion equations. Stochastics and Partial Differential Equations:
Analysis and Computations. 2024;12:1907-1981. doi:10.1007/s40072-023-00319-4'
apa: 'Agresti, A. (2024). Delayed blow-up and enhanced diffusion by transport noise
for systems of reaction-diffusion equations. Stochastics and Partial Differential
Equations: Analysis and Computations. Springer Nature. https://doi.org/10.1007/s40072-023-00319-4'
chicago: 'Agresti, Antonio. “Delayed Blow-up and Enhanced Diffusion by Transport
Noise for Systems of Reaction-Diffusion Equations.” Stochastics and Partial
Differential Equations: Analysis and Computations. Springer Nature, 2024.
https://doi.org/10.1007/s40072-023-00319-4.'
ieee: 'A. Agresti, “Delayed blow-up and enhanced diffusion by transport noise for
systems of reaction-diffusion equations,” Stochastics and Partial Differential
Equations: Analysis and Computations, vol. 12. Springer Nature, pp. 1907–1981,
2024.'
ista: 'Agresti A. 2024. Delayed blow-up and enhanced diffusion by transport noise
for systems of reaction-diffusion equations. Stochastics and Partial Differential
Equations: Analysis and Computations. 12, 1907–1981.'
mla: 'Agresti, Antonio. “Delayed Blow-up and Enhanced Diffusion by Transport Noise
for Systems of Reaction-Diffusion Equations.” Stochastics and Partial Differential
Equations: Analysis and Computations, vol. 12, Springer Nature, 2024, pp.
1907–81, doi:10.1007/s40072-023-00319-4.'
short: 'A. Agresti, Stochastics and Partial Differential Equations: Analysis and
Computations 12 (2024) 1907–1981.'
corr_author: '1'
das_tickbox: '1'
dataavailabilitystatement: This manuscript has no associated data.
date_created: 2023-02-02T10:45:47Z
date_published: 2024-09-01T00:00:00Z
date_updated: 2026-10-15T09:48:09Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s40072-023-00319-4
ec_funded: 1
external_id:
arxiv:
- '2207.08293'
isi:
- '001108594600001'
pmid:
- '39104877'
file:
- access_level: open_access
checksum: 3c93d07a5f7e0b0caa8062eadcfa69c2
content_type: application/pdf
creator: dernst
date_created: 2025-01-09T08:01:02Z
date_updated: 2025-01-09T08:01:02Z
file_id: '18787'
file_name: 2024_StochPartDiffEquations_Agresti.pdf
file_size: 1320682
relation: main_file
success: 1
file_date_updated: 2025-01-09T08:01:02Z
fulldoi: https://doi.org/10.1007/s40072-023-00319-4
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 1907-1981
pmid: 1
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: 'Stochastics and Partial Differential Equations: Analysis and Computations'
publication_identifier:
eissn:
- 2194-041X
issn:
- 2194-0401
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: no
title: Delayed blow-up and enhanced diffusion by transport noise for systems of reaction-diffusion
equations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 12
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '14797'
abstract:
- lang: eng
text: We study a random matching problem on closed compact 2 -dimensional Riemannian
manifolds (with respect to the squared Riemannian distance), with samples of random
points whose common law is absolutely continuous with respect to the volume measure
with strictly positive and bounded density. We show that given two sequences of
numbers n and m=m(n) of points, asymptotically equivalent as n goes to infinity,
the optimal transport plan between the two empirical measures μn and νm is
quantitatively well-approximated by (Id,exp(∇hn))#μn where hn solves a linear
elliptic PDE obtained by a regularized first-order linearization of the Monge-Ampère
equation. This is obtained in the case of samples of correlated random points
for which a stretched exponential decay of the α -mixing coefficient holds and
for a class of discrete-time Markov chains having a unique absolutely continuous
invariant measure with respect to the volume measure.
acknowledgement: "NC has received funding from the European Research Council (ERC)
under the European Union’s Horizon 2020 research and innovation programme (Grant
agreement No 948819).\r\nFM is supported by the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation) through the SPP 2265 Random Geometric Systems.
FM has been funded by the Deutsche Forschungsgemeinschaft (DFG, German Research
Foundation) under Germany’s Excellence Strategy EXC 2044 -390685587, Mathematics
Münster: Dynamics–Geometry–Structure. FM has been funded by the Max Planck Institute
for Mathematics in the Sciences."
article_processing_charge: Yes (in subscription journal)
article_type: original
arxiv: 1
author:
- first_name: Nicolas
full_name: Clozeau, Nicolas
id: fea1b376-906f-11eb-847d-b2c0cf46455b
last_name: Clozeau
- first_name: Francesco
full_name: Mattesini, Francesco
last_name: Mattesini
citation:
ama: Clozeau N, Mattesini F. Annealed quantitative estimates for the quadratic 2D-discrete
random matching problem. Probability Theory and Related Fields. 2024;190:485-541.
doi:10.1007/s00440-023-01254-0
apa: Clozeau, N., & Mattesini, F. (2024). Annealed quantitative estimates for
the quadratic 2D-discrete random matching problem. Probability Theory and Related
Fields. Springer Nature. https://doi.org/10.1007/s00440-023-01254-0
chicago: Clozeau, Nicolas, and Francesco Mattesini. “Annealed Quantitative Estimates
for the Quadratic 2D-Discrete Random Matching Problem.” Probability Theory
and Related Fields. Springer Nature, 2024. https://doi.org/10.1007/s00440-023-01254-0.
ieee: N. Clozeau and F. Mattesini, “Annealed quantitative estimates for the quadratic
2D-discrete random matching problem,” Probability Theory and Related Fields,
vol. 190. Springer Nature, pp. 485–541, 2024.
ista: Clozeau N, Mattesini F. 2024. Annealed quantitative estimates for the quadratic
2D-discrete random matching problem. Probability Theory and Related Fields. 190,
485–541.
mla: Clozeau, Nicolas, and Francesco Mattesini. “Annealed Quantitative Estimates
for the Quadratic 2D-Discrete Random Matching Problem.” Probability Theory
and Related Fields, vol. 190, Springer Nature, 2024, pp. 485–541, doi:10.1007/s00440-023-01254-0.
short: N. Clozeau, F. Mattesini, Probability Theory and Related Fields 190 (2024)
485–541.
corr_author: '1'
das_tickbox: '0'
date_created: 2024-01-14T23:00:57Z
date_published: 2024-10-01T00:00:00Z
date_updated: 2026-10-15T09:48:31Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s00440-023-01254-0
ec_funded: 1
external_id:
arxiv:
- '2303.00353'
isi:
- '001136206200002'
file:
- access_level: open_access
checksum: 34f44cad6a210ff66791ee37e590af2c
content_type: application/pdf
creator: dernst
date_created: 2025-01-09T08:10:54Z
date_updated: 2025-01-09T08:10:54Z
file_id: '18788'
file_name: 2024_ProbTheoryRelatFields_Clozeau.pdf
file_size: 880117
relation: main_file
success: 1
file_date_updated: 2025-01-09T08:10:54Z
fulldoi: https://doi.org/10.1007/s00440-023-01254-0
has_accepted_license: '1'
intvolume: ' 190'
isi: 1
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 485-541
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Probability Theory and Related Fields
publication_identifier:
eissn:
- 1432-2064
issn:
- 0178-8051
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Annealed quantitative estimates for the quadratic 2D-discrete random matching
problem
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 190
year: '2024'
...
---
_id: '15334'
abstract:
- lang: eng
text: We consider the sharp interface limit of a Navier-Stokes/Allen Cahn equation
in a bounded smooth domain in two space dimensions, in the case of vanishing mobility
mε=ε√, where the small parameter ε>0 related to the thickness of the diffuse interface
is sent to zero. For well-prepared initial data and sufficiently small times,
we rigorously prove convergence to the classical two-phase Navier-Stokes system
with surface tension. The idea of the proof is to use asymptotic expansions to
construct an approximate solution and to estimate the difference of the exact
and approximate solutions with a spectral estimate for the (at the approximate
solution) linearized Allen-Cahn operator. In the calculations we use a fractional
order ansatz and new ansatz terms in higher orders leading to a suitable ε-scaled
and coupled model problem. Moreover, we apply the novel idea of introducing ε-dependent
coordinates.
acknowledgement: "Open Access funding enabled and organized by Projekt DEAL.\r\nM.
Fei was partially supported by NSF of China under Grant No. 12271004 and Anhui Provincial
Funding Project under Grant Nos. gxbjZD2022009 and 2308085J10. Moreover, M. Moser
has received funding from the European Research Council (ERC) under the European
Union’s Horizon 2020 research and innovation programme (Grant Agreement No 948819)."
article_number: '94'
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Helmut
full_name: Abels, Helmut
last_name: Abels
- first_name: Mingwen
full_name: Fei, Mingwen
last_name: Fei
- first_name: Maximilian
full_name: Moser, Maximilian
id: a60047a9-da77-11eb-85b4-c4dc385ebb8c
last_name: Moser
citation:
ama: Abels H, Fei M, Moser M. Sharp interface limit for a Navier–Stokes/Allen–Cahn
system in the case of a vanishing mobility. Calculus of Variations and Partial
Differential Equations. 2024;63(4). doi:10.1007/s00526-024-02715-7
apa: Abels, H., Fei, M., & Moser, M. (2024). Sharp interface limit for a Navier–Stokes/Allen–Cahn
system in the case of a vanishing mobility. Calculus of Variations and Partial
Differential Equations. Springer Nature. https://doi.org/10.1007/s00526-024-02715-7
chicago: Abels, Helmut, Mingwen Fei, and Maximilian Moser. “Sharp Interface Limit
for a Navier–Stokes/Allen–Cahn System in the Case of a Vanishing Mobility.” Calculus
of Variations and Partial Differential Equations. Springer Nature, 2024. https://doi.org/10.1007/s00526-024-02715-7.
ieee: H. Abels, M. Fei, and M. Moser, “Sharp interface limit for a Navier–Stokes/Allen–Cahn
system in the case of a vanishing mobility,” Calculus of Variations and Partial
Differential Equations, vol. 63, no. 4. Springer Nature, 2024.
ista: Abels H, Fei M, Moser M. 2024. Sharp interface limit for a Navier–Stokes/Allen–Cahn
system in the case of a vanishing mobility. Calculus of Variations and Partial
Differential Equations. 63(4), 94.
mla: Abels, Helmut, et al. “Sharp Interface Limit for a Navier–Stokes/Allen–Cahn
System in the Case of a Vanishing Mobility.” Calculus of Variations and Partial
Differential Equations, vol. 63, no. 4, 94, Springer Nature, 2024, doi:10.1007/s00526-024-02715-7.
short: H. Abels, M. Fei, M. Moser, Calculus of Variations and Partial Differential
Equations 63 (2024).
das_tickbox: '0'
date_created: 2024-04-21T22:00:52Z
date_published: 2024-05-01T00:00:00Z
date_updated: 2026-10-15T09:47:15Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s00526-024-02715-7
ec_funded: 1
external_id:
arxiv:
- '2304.12096'
isi:
- '001199418100002'
file:
- access_level: open_access
checksum: b1095fad4cae596f52cc616a973bdde2
content_type: application/pdf
creator: dernst
date_created: 2024-04-23T07:30:48Z
date_updated: 2024-04-23T07:30:48Z
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file_size: 975186
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file_date_updated: 2024-04-23T07:30:48Z
fulldoi: https://doi.org/10.1007/s00526-024-02715-7
has_accepted_license: '1'
intvolume: ' 63'
isi: 1
issue: '4'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Published Version
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Calculus of Variations and Partial Differential Equations
publication_identifier:
eissn:
- 1432-0835
issn:
- 0944-2669
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Sharp interface limit for a Navier–Stokes/Allen–Cahn system in the case of
a vanishing mobility
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 63
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '19007'
abstract:
- lang: eng
text: "Learning modular object-centric representations is crucial for systematic
generalization. Existing methods show promising object-binding capabilities empirically,\r\nbut
theoretical identifiability guarantees remain relatively underdeveloped. Understanding
when object-centric representations can theoretically be identified is\r\ncrucial
for scaling slot-based methods to high-dimensional images with correctness\r\nguarantees.
To that end, we propose a probabilistic slot-attention algorithm that\r\nimposes
an aggregate mixture prior over object-centric slot representations, thereby\r\nproviding
slot identifiability guarantees without supervision, up to an equivalence\r\nrelation.
We provide empirical verification of our theoretical identifiability result\r\nusing
both simple 2-dimensional data and high-resolution imaging datasets.\r\n"
acknowledgement: A. Kori is supported by UKRI (grant number EP/S023356/1), as part
of the UKRI Centre for Doctoral Training in Safe and Trusted AI. B. Glocker and
F.D.S. Ribeiro acknowledge the support of the UKRI AI programme, and the Engineering
and Physical Sciences Research Council, for CHAI - EPSRC Causality in Healthcare
AI Hub (grant number EP/Y028856/1).
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Avinash
full_name: Kori, Avinash
last_name: Kori
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Ainkaran
full_name: Santhirasekaram, Ainkaran
last_name: Santhirasekaram
- first_name: Francesca
full_name: Toni, Francesca
last_name: Toni
- first_name: Ben
full_name: Glocker, Ben
last_name: Glocker
- first_name: Fabio
full_name: De Sousa Ribeiro, Fabio
last_name: De Sousa Ribeiro
citation:
ama: 'Kori A, Locatello F, Santhirasekaram A, Toni F, Glocker B, De Sousa Ribeiro
F. Identifiable object-centric representation learning via probabilistic slot
attention. In: 38th Conference on Neural Information Processing Systems.
Vol 37. Neural Information Processing Systems Foundation; 2024. doi:10.52202/079017-2960'
apa: 'Kori, A., Locatello, F., Santhirasekaram, A., Toni, F., Glocker, B., &
De Sousa Ribeiro, F. (2024). Identifiable object-centric representation learning
via probabilistic slot attention. In 38th Conference on Neural Information
Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing
Systems Foundation. https://doi.org/10.52202/079017-2960'
chicago: Kori, Avinash, Francesco Locatello, Ainkaran Santhirasekaram, Francesca
Toni, Ben Glocker, and Fabio De Sousa Ribeiro. “Identifiable Object-Centric Representation
Learning via Probabilistic Slot Attention.” In 38th Conference on Neural Information
Processing Systems, Vol. 37. Neural Information Processing Systems Foundation,
2024. https://doi.org/10.52202/079017-2960.
ieee: A. Kori, F. Locatello, A. Santhirasekaram, F. Toni, B. Glocker, and F. De
Sousa Ribeiro, “Identifiable object-centric representation learning via probabilistic
slot attention,” in 38th Conference on Neural Information Processing Systems,
Vancouver, Canada, 2024, vol. 37.
ista: 'Kori A, Locatello F, Santhirasekaram A, Toni F, Glocker B, De Sousa Ribeiro
F. 2024. Identifiable object-centric representation learning via probabilistic
slot attention. 38th Conference on Neural Information Processing Systems. NeurIPS:
Neural Information Processing Systems, Advances in Neural Information Processing
Systems, vol. 37.'
mla: Kori, Avinash, et al. “Identifiable Object-Centric Representation Learning
via Probabilistic Slot Attention.” 38th Conference on Neural Information Processing
Systems, vol. 37, Neural Information Processing Systems Foundation, 2024,
doi:10.52202/079017-2960.
short: A. Kori, F. Locatello, A. Santhirasekaram, F. Toni, B. Glocker, F. De Sousa
Ribeiro, in:, 38th Conference on Neural Information Processing Systems, Neural
Information Processing Systems Foundation, 2024.
conference:
end_date: 2024-12-16
location: Vancouver, Canada
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2024-12-16
das_tickbox: '0'
date_created: 2025-02-05T08:36:22Z
date_published: 2024-12-01T00:00:00Z
date_updated: 2026-10-15T09:48:32Z
day: '01'
ddc:
- '000'
department:
- _id: FrLo
doi: 10.52202/079017-2960
external_id:
arxiv:
- '2406.07141'
file:
- access_level: open_access
checksum: d27b3c7102adc28e798fe41001f0b919
content_type: application/pdf
creator: dernst
date_created: 2025-02-05T08:34:25Z
date_updated: 2025-02-05T08:34:25Z
file_id: '19008'
file_name: 2024_NeurIPS_Kori.pdf
file_size: 6943800
relation: main_file
success: 1
file_date_updated: 2025-02-05T08:34:25Z
fulldoi: https://doi.org/10.52202/079017-2960
has_accepted_license: '1'
intvolume: ' 37'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: 38th Conference on Neural Information Processing Systems
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Identifiable object-centric representation learning via probabilistic slot
attention
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...
---
OA_place: publisher
OA_type: hybrid
_id: '15098'
abstract:
- lang: eng
text: The paper is devoted to the analysis of the global well-posedness and the
interior regularity of the 2D Navier–Stokes equations with inhomogeneous stochastic
boundary conditions. The noise, white in time and coloured in space, can be interpreted
as the physical law describing the driving mechanism on the atmosphere–ocean interface,
i.e. as a balance of the shear stress of the ocean and the horizontal wind force.
acknowledgement: The authors thank Professor Franco Flandoli for useful discussions
and valuable insight into the subject. In particular, A.A. would like to thank professor
Franco Flandoli for hosting and financially contributing to his research visit at
Scuola Normale di Pisa in January 2023, where this work started. E.L. would like
to express sincere gratitude to Professor Marco Fuhrman for igniting his interest
in this particular field of research. E.L. want to thank Professor Matthias Hieber
and Dr. Martin Saal for useful discussions. Finally, the authors thank the anonymous
referee for helpful comments which improved the paper from its initial version.Open
access funding provided by Scuola Normale Superiore within the CRUI-CARE Agreement.
A. Agresti has received funding from the European Research Council (ERC) under the
European Union’s Horizon 2020 research and innovation programme (Grant Agreement
No. 948819).
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
- first_name: Eliseo
full_name: Luongo, Eliseo
last_name: Luongo
citation:
ama: Agresti A, Luongo E. Global well-posedness and interior regularity of 2D Navier-Stokes
equations with stochastic boundary conditions. Mathematische Annalen. 2024;390:2727-2766.
doi:10.1007/s00208-024-02812-0
apa: Agresti, A., & Luongo, E. (2024). Global well-posedness and interior regularity
of 2D Navier-Stokes equations with stochastic boundary conditions. Mathematische
Annalen. Springer Nature. https://doi.org/10.1007/s00208-024-02812-0
chicago: Agresti, Antonio, and Eliseo Luongo. “Global Well-Posedness and Interior
Regularity of 2D Navier-Stokes Equations with Stochastic Boundary Conditions.”
Mathematische Annalen. Springer Nature, 2024. https://doi.org/10.1007/s00208-024-02812-0.
ieee: A. Agresti and E. Luongo, “Global well-posedness and interior regularity of
2D Navier-Stokes equations with stochastic boundary conditions,” Mathematische
Annalen, vol. 390. Springer Nature, pp. 2727–2766, 2024.
ista: Agresti A, Luongo E. 2024. Global well-posedness and interior regularity of
2D Navier-Stokes equations with stochastic boundary conditions. Mathematische
Annalen. 390, 2727–2766.
mla: Agresti, Antonio, and Eliseo Luongo. “Global Well-Posedness and Interior Regularity
of 2D Navier-Stokes Equations with Stochastic Boundary Conditions.” Mathematische
Annalen, vol. 390, Springer Nature, 2024, pp. 2727–66, doi:10.1007/s00208-024-02812-0.
short: A. Agresti, E. Luongo, Mathematische Annalen 390 (2024) 2727–2766.
das_tickbox: '1'
dataavailabilitystatement: Data sharing not applicable to this article as no data
sets were generated or analyzed during the current study.
date_created: 2024-03-10T23:00:54Z
date_published: 2024-10-01T00:00:00Z
date_updated: 2026-10-15T09:48:57Z
day: '01'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.1007/s00208-024-02812-0
ec_funded: 1
external_id:
arxiv:
- '2306.11081'
isi:
- '001172711400002'
pmid:
- '39351582'
file:
- access_level: open_access
checksum: d55cac8bddea09a97f06612825c4f229
content_type: application/pdf
creator: dernst
date_created: 2025-01-09T08:23:36Z
date_updated: 2025-01-09T08:23:36Z
file_id: '18790'
file_name: 2024_MathAnnalen_Agresti.pdf
file_size: 661557
relation: main_file
success: 1
file_date_updated: 2025-01-09T08:23:36Z
fulldoi: https://doi.org/10.1007/s00208-024-02812-0
has_accepted_license: '1'
intvolume: ' 390'
isi: 1
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 2727-2766
pmid: 1
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Mathematische Annalen
publication_identifier:
eissn:
- 1432-1807
issn:
- 0025-5831
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
researchdata_availability: not applicable
scopus_import: '1'
status: public
supplementarymaterial: no
title: Global well-posedness and interior regularity of 2D Navier-Stokes equations
with stochastic boundary conditions
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 390
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '17462'
abstract:
- lang: eng
text: We are interested in numerical algorithms for computing the electrical field
generated by a charge distribution localized on scale l in an infinite heterogeneous
correlated random medium, in a situation where the medium is only known in a box
of diameter L >>l around the support of the charge. We show that the algorithm
in [J. Lu, F. Otto, and L. Wang, Optimal Artificial Boundary Conditions Based
on Second-Order Correctors for Three Dimensional Random Ellilptic Media, preprint,
arXiv:2109.01616, 2021], suggesting optimal Dirichlet boundary conditions motivated
by the multipole expansion [P. Bella, A. Giunti, and F. Otto, Comm. Partial Differential
Equations, 45 (2020), pp. 561–640], still performs well in correlated media. With
overwhelming probability, we obtain a convergence rate in terms of l, L, and the
size of the correlations for which optimality is supported with numerical simulations.
These estimates are provided for ensembles which satisfy a multiscale logarithmic
Sobolev inequality, where our main tool is an extension of the semigroup estimates
in [N. Clozeau, Stoch. Partial Differ. Equ. Anal. Comput., 11 (2023), pp. 1254–1378].
As part of our strategy, we construct sublinear second-order correctors in this
correlated setting, which is of independent interest.
acknowledgement: We would like to thank our affiliations, Institute of Science and
Technology Austria and Max Planck Institute for Mathematics in the Sciences, for
supporting the authors’ visits to each other, which greatly facilitated this work.
We would like to thank Marc Josien and Quinn Winters for assistance in numerical
implementation.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Nicolas
full_name: Clozeau, Nicolas
id: fea1b376-906f-11eb-847d-b2c0cf46455b
last_name: Clozeau
- first_name: Lihan
full_name: Wang, Lihan
last_name: Wang
citation:
ama: Clozeau N, Wang L. Artificial boundary conditions for random elliptic systems
with correlated coefficient field. Multiscale Modeling and Simulation.
2024;22(3):973-1029. doi:10.1137/23M1603819
apa: Clozeau, N., & Wang, L. (2024). Artificial boundary conditions for random
elliptic systems with correlated coefficient field. Multiscale Modeling and
Simulation. Society for Industrial and Applied Mathematics. https://doi.org/10.1137/23M1603819
chicago: Clozeau, Nicolas, and Lihan Wang. “Artificial Boundary Conditions for Random
Elliptic Systems with Correlated Coefficient Field.” Multiscale Modeling and
Simulation. Society for Industrial and Applied Mathematics, 2024. https://doi.org/10.1137/23M1603819.
ieee: N. Clozeau and L. Wang, “Artificial boundary conditions for random elliptic
systems with correlated coefficient field,” Multiscale Modeling and Simulation,
vol. 22, no. 3. Society for Industrial and Applied Mathematics, pp. 973–1029,
2024.
ista: Clozeau N, Wang L. 2024. Artificial boundary conditions for random elliptic
systems with correlated coefficient field. Multiscale Modeling and Simulation.
22(3), 973–1029.
mla: Clozeau, Nicolas, and Lihan Wang. “Artificial Boundary Conditions for Random
Elliptic Systems with Correlated Coefficient Field.” Multiscale Modeling and
Simulation, vol. 22, no. 3, Society for Industrial and Applied Mathematics,
2024, pp. 973–1029, doi:10.1137/23M1603819.
short: N. Clozeau, L. Wang, Multiscale Modeling and Simulation 22 (2024) 973–1029.
corr_author: '1'
das_tickbox: '0'
date_created: 2024-08-25T22:01:08Z
date_published: 2024-09-01T00:00:00Z
date_updated: 2026-10-15T09:49:19Z
day: '01'
department:
- _id: JuFi
doi: 10.1137/23M1603819
ec_funded: 1
external_id:
arxiv:
- '2309.06798'
isi:
- '001285416500001'
fulldoi: https://doi.org/10.1137/23M1603819
intvolume: ' 22'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2309.06798
month: '09'
oa: 1
oa_version: Preprint
page: 973-1029
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Multiscale Modeling and Simulation
publication_identifier:
eissn:
- 1540-3467
issn:
- 1540-3459
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Artificial boundary conditions for random elliptic systems with correlated
coefficient field
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 22
year: '2024'
...
---
_id: '15119'
abstract:
- lang: eng
text: In this paper we consider an SPDE where the leading term is a second order
operator with periodic boundary conditions, coefficients which are measurable
in (t,ω) , and Hölder continuous in space. Assuming stochastic parabolicity conditions,
we prove Lp((0,T)×Ω,tκdt;Hσ,q(Td)) -estimates. The main novelty is that we do
not require p=q . Moreover, we allow arbitrary σ∈R and weights in time. Such
mixed regularity estimates play a crucial role in applications to nonlinear SPDEs
which is clear from our previous work. To prove our main results we develop a
general perturbation theory for SPDEs. Moreover, we prove a new result on pointwise
multiplication in spaces with fractional smoothness.
acknowledgement: The first author has been partially supported by the Nachwuchsring
– Network for the promotion of young scientists – at TU Kaiserslautern. The second
author is supported by the VIDI subsidy 639.032.427 of the Netherlands Organisation
for Scientific Research (NWO). The authors thank the anonymous referees and Max
Sauerbrey for careful reading and helpful suggestions.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Antonio
full_name: Agresti, Antonio
id: 673cd0cc-9b9a-11eb-b144-88f30e1fbb72
last_name: Agresti
orcid: 0000-0002-9573-2962
- first_name: Mark
full_name: Veraar, Mark
last_name: Veraar
citation:
ama: Agresti A, Veraar M. Stochastic maximal Lp(Lq)-regularity for second order
systems with periodic boundary conditions. Annales de l’Institut Henri Poincaré,
Probabilités et Statistiques. 2024;60(1):413-430. doi:10.1214/22-AIHP1333
apa: Agresti, A., & Veraar, M. (2024). Stochastic maximal Lp(Lq)-regularity
for second order systems with periodic boundary conditions. Annales de l’Institut
Henri Poincaré, Probabilités et Statistiques. Institute of Mathematical Statistics.
https://doi.org/10.1214/22-AIHP1333
chicago: Agresti, Antonio, and Mark Veraar. “Stochastic Maximal Lp(Lq)-Regularity
for Second Order Systems with Periodic Boundary Conditions.” Annales de l’Institut
Henri Poincaré, Probabilités et Statistiques. Institute of Mathematical Statistics,
2024. https://doi.org/10.1214/22-AIHP1333.
ieee: A. Agresti and M. Veraar, “Stochastic maximal Lp(Lq)-regularity for second
order systems with periodic boundary conditions,” Annales de l’Institut Henri
Poincaré, Probabilités et Statistiques, vol. 60, no. 1. Institute of Mathematical
Statistics, pp. 413–430, 2024.
ista: Agresti A, Veraar M. 2024. Stochastic maximal Lp(Lq)-regularity for second
order systems with periodic boundary conditions. Annales de l’Institut Henri Poincaré,
Probabilités et Statistiques. 60(1), 413–430.
mla: Agresti, Antonio, and Mark Veraar. “Stochastic Maximal Lp(Lq)-Regularity for
Second Order Systems with Periodic Boundary Conditions.” Annales de l’Institut
Henri Poincaré, Probabilités et Statistiques, vol. 60, no. 1, Institute of
Mathematical Statistics, 2024, pp. 413–30, doi:10.1214/22-AIHP1333.
short: A. Agresti, M. Veraar, Annales de l’Institut Henri Poincaré, Probabilités
et Statistiques 60 (2024) 413–430.
corr_author: '1'
das_tickbox: '0'
date_created: 2024-03-17T23:00:58Z
date_published: 2024-02-01T00:00:00Z
date_updated: 2026-10-15T09:46:19Z
day: '01'
department:
- _id: JuFi
doi: 10.1214/22-AIHP1333
external_id:
arxiv:
- '2106.01274'
fulldoi: https://doi.org/10.1214/22-AIHP1333
intvolume: ' 60'
issue: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2106.01274
month: '02'
oa: 1
oa_version: Preprint
page: 413-430
publication: Annales de l'Institut Henri Poincaré, Probabilités et Statistiques
publication_identifier:
issn:
- 0246-0203
publication_status: published
publisher: Institute of Mathematical Statistics
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Stochastic maximal Lp(Lq)-regularity for second order systems with periodic
boundary conditions
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 60
year: '2024'
...
---
_id: '17481'
abstract:
- lang: eng
text: "Phase-field models such as the Allen–Cahn equation may give rise to the formation
and evolution of geometric shapes, a phenomenon that may be analyzed rigorously
in suitable scaling regimes. In its sharp-interface limit, the vectorial Allen–Cahn
equation with a potential with N≥3 distinct minima has been conjectured to describe
the evolution of branched interfaces by multiphase mean curvature flow. In the
present work, we give a rigorous proof for this statement in two and three ambient
dimensions and for a suitable class of potentials: as long as a strong solution
to multiphase mean curvature flow exists, solutions to the vectorial Allen–Cahn
equation with well-prepared initial data converge towards multiphase mean curvature
flow in the limit of vanishing interface width parameter ε↘0. We even establish
the rate of convergence O(ε \r\n1/2\r\n ). Our approach is based on the gradient-flow
structure of the Allen–Cahn equation and its limiting motion: building on the
recent concept of “gradient-flow calibrations” for multiphase mean curvature flow,
we introduce a notion of relative entropy for the vectorial Allen–Cahn equation
with multi-well potential. This enables us to overcome the limitations of other
approaches, e.g. avoiding the need for a stability analysis of the Allen–Cahn
operator or additional convergence hypotheses for the energy at positive times."
acknowledgement: "The authors thank Sebastian Hensel for useful and helpful commentson
the first draft of this work.\r\nThis project has received funding from the European
Research Council (ERC)\r\nunder the European Union’s Horizon 2020 research and innovation
programme (grant\r\nagreement no. 948819."
article_processing_charge: Yes
article_type: original
author:
- first_name: Julian L
full_name: Fischer, Julian L
id: 2C12A0B0-F248-11E8-B48F-1D18A9856A87
last_name: Fischer
orcid: 0000-0002-0479-558X
- first_name: Alice
full_name: Marveggio, Alice
id: 25647992-AA84-11E9-9D75-8427E6697425
last_name: Marveggio
citation:
ama: Fischer JL, Marveggio A. Quantitative convergence of the vectorial Allen–Cahn
equation towards multiphase mean curvature flow. Annales de l’Institut Henri
Poincaré C. 2024;41(5):1117-1178. doi:10.4171/AIHPC/109
apa: Fischer, J. L., & Marveggio, A. (2024). Quantitative convergence of the
vectorial Allen–Cahn equation towards multiphase mean curvature flow. Annales
de l’Institut Henri Poincaré C. EMS Press. https://doi.org/10.4171/AIHPC/109
chicago: Fischer, Julian L, and Alice Marveggio. “Quantitative Convergence of the
Vectorial Allen–Cahn Equation towards Multiphase Mean Curvature Flow.” Annales
de l’Institut Henri Poincaré C. EMS Press, 2024. https://doi.org/10.4171/AIHPC/109.
ieee: J. L. Fischer and A. Marveggio, “Quantitative convergence of the vectorial
Allen–Cahn equation towards multiphase mean curvature flow,” Annales de l’Institut
Henri Poincaré C, vol. 41, no. 5. EMS Press, pp. 1117–1178, 2024.
ista: Fischer JL, Marveggio A. 2024. Quantitative convergence of the vectorial Allen–Cahn
equation towards multiphase mean curvature flow. Annales de l’Institut Henri Poincaré
C. 41(5), 1117–1178.
mla: Fischer, Julian L., and Alice Marveggio. “Quantitative Convergence of the Vectorial
Allen–Cahn Equation towards Multiphase Mean Curvature Flow.” Annales de l’Institut
Henri Poincaré C, vol. 41, no. 5, EMS Press, 2024, pp. 1117–78, doi:10.4171/AIHPC/109.
short: J.L. Fischer, A. Marveggio, Annales de l’Institut Henri Poincaré C 41 (2024)
1117–1178.
corr_author: '1'
das_tickbox: '0'
date_created: 2024-09-01T22:01:09Z
date_published: 2024-01-24T00:00:00Z
date_updated: 2026-10-15T09:49:35Z
day: '24'
ddc:
- '510'
department:
- _id: JuFi
doi: 10.4171/AIHPC/109
ec_funded: 1
external_id:
isi:
- '001293853900003'
file:
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checksum: b5ad02d9abd5b4701269cd1ad0a1cc8f
content_type: application/pdf
creator: dernst
date_created: 2024-09-09T07:46:42Z
date_updated: 2024-09-09T07:46:42Z
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file_name: 2024_AnnInstHPoincare_Fischer.pdf
file_size: 1348896
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fulldoi: https://doi.org/10.4171/AIHPC/109
has_accepted_license: '1'
intvolume: ' 41'
isi: 1
issue: '5'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 1117-1178
project:
- _id: 0aa76401-070f-11eb-9043-b5bb049fa26d
call_identifier: H2020
grant_number: '948819'
name: Bridging Scales in Random Materials
publication: Annales de l'Institut Henri Poincaré C
publication_identifier:
eissn:
- 1873-1430
issn:
- 0294-1449
publication_status: published
publisher: EMS Press
quality_controlled: '1'
related_material:
record:
- id: '14597'
relation: earlier_version
status: public
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Quantitative convergence of the vectorial Allen–Cahn equation towards multiphase
mean curvature flow
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 41
year: '2024'
...
---
_id: '17098'
abstract:
- lang: eng
text: Turn-based discounted-sum games are two-player zero-sum games played on finite
directed graphs. The vertices of the graph are partitioned between player 1 and
player 2. Plays are infinite walks on the graph where the next vertex is decided
by a player that owns the current vertex. Each edge is assigned an integer weight
and the payoff of a play is the discounted-sum of the weights of the play. The
goal of player 1 is to maximize the discounted-sum payoff against the adversarial
player 2. These games lie in NP ∩ coNP and are among the rare combinatorial problems
that belong to this complexity class and the existence of a polynomial-time algorithm
is a major open question. Since breaking the general exponential barrier has been
a challenging problem, faster parameterized algorithms have been considered. If
the discount factor is expressed in unary, then discounted-sum games can be solved
in polynomial time. However, if the discount factor is arbitrary (or expressed
in binary), but the weights are in unary, none of the existing approaches yield
a sub-exponential bound. Our main result is a new analysis technique for a classical
algorithm (namely, the strategy iteration algorithm) that present a new runtime
bound which is [EQUATION] for game graphs with n vertices and absolute weights
of at most W. In particular, our result yields a deterministic sub-exponential
bound for games with weights that are constant or represented in unary.
acknowledgement: "This research was partially supported by the ERC CoG 863818 (ForM-SMArt)
grant.\r\n"
article_number: '6'
article_processing_charge: No
arxiv: 1
author:
- first_name: Ali
full_name: Asadi, Ali
id: 02d96aae-000e-11ec-b801-cadd0a5eefbb
last_name: Asadi
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Raimundo J
full_name: Saona Urmeneta, Raimundo J
id: BD1DF4C4-D767-11E9-B658-BC13E6697425
last_name: Saona Urmeneta
orcid: 0000-0001-5103-038X
citation:
ama: 'Asadi A, Chatterjee K, Svoboda J, Saona Urmeneta RJ. Deterministic sub-exponential
algorithm for discounted-sum games with unary weights. In: 39th Annual ACM/IEEE
Symposium on Logic in Computer Science. Association for Computing Machinery;
2024. doi:10.1145/3661814.3662080'
apa: 'Asadi, A., Chatterjee, K., Svoboda, J., & Saona Urmeneta, R. J. (2024).
Deterministic sub-exponential algorithm for discounted-sum games with unary weights.
In 39th Annual ACM/IEEE Symposium on Logic in Computer Science. Tallinn,
Estonia: Association for Computing Machinery. https://doi.org/10.1145/3661814.3662080'
chicago: Asadi, Ali, Krishnendu Chatterjee, Jakub Svoboda, and Raimundo J Saona
Urmeneta. “Deterministic Sub-Exponential Algorithm for Discounted-Sum Games with
Unary Weights.” In 39th Annual ACM/IEEE Symposium on Logic in Computer Science.
Association for Computing Machinery, 2024. https://doi.org/10.1145/3661814.3662080.
ieee: A. Asadi, K. Chatterjee, J. Svoboda, and R. J. Saona Urmeneta, “Deterministic
sub-exponential algorithm for discounted-sum games with unary weights,” in 39th
Annual ACM/IEEE Symposium on Logic in Computer Science, Tallinn, Estonia,
2024.
ista: 'Asadi A, Chatterjee K, Svoboda J, Saona Urmeneta RJ. 2024. Deterministic
sub-exponential algorithm for discounted-sum games with unary weights. 39th Annual
ACM/IEEE Symposium on Logic in Computer Science. LICS: Logic in Computer Science,
6.'
mla: Asadi, Ali, et al. “Deterministic Sub-Exponential Algorithm for Discounted-Sum
Games with Unary Weights.” 39th Annual ACM/IEEE Symposium on Logic in Computer
Science, 6, Association for Computing Machinery, 2024, doi:10.1145/3661814.3662080.
short: A. Asadi, K. Chatterjee, J. Svoboda, R.J. Saona Urmeneta, in:, 39th Annual
ACM/IEEE Symposium on Logic in Computer Science, Association for Computing Machinery,
2024.
conference:
end_date: 2024-07-11
location: Tallinn, Estonia
name: 'LICS: Logic in Computer Science'
start_date: 2024-07-08
corr_author: '1'
das_tickbox: '0'
date_created: 2024-06-03T07:43:15Z
date_published: 2024-07-08T00:00:00Z
date_updated: 2026-10-15T09:51:23Z
day: '08'
department:
- _id: KrCh
doi: 10.1145/3661814.3662080
ec_funded: 1
external_id:
arxiv:
- '2405.02479'
isi:
- '001275042100006'
fulldoi: https://doi.org/10.1145/3661814.3662080
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2405.02479
month: '07'
oa: 1
oa_version: Preprint
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 39th Annual ACM/IEEE Symposium on Logic in Computer Science
publication_identifier:
eissn:
- 1043-6871
isbn:
- '9798400706608'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
researchdata_availability: no
scopus_import: '1'
status: public
supplementarymaterial: no
title: Deterministic sub-exponential algorithm for discounted-sum games with unary
weights
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
year: '2024'
...
---
OA_place: repository
OA_type: green
_id: '19510'
abstract:
- lang: eng
text: "We propose a new variant of the Adam optimizer [Kingma and Ba, 2014] called\r\nMICROADAM
that specifically minimizes memory overheads, while maintaining\r\ntheoretical
convergence guarantees. We achieve this by compressing the gradient\r\ninformation
before it is fed into the optimizer state, thereby reducing its memory\r\nfootprint
significantly. We control the resulting compression error via a novel\r\ninstance
of the classical error feedback mechanism from distributed optimization [Seide
et al., 2014, Alistarh et al., 2018, Karimireddy et al., 2019] in which\r\nthe
error correction information is itself compressed to allow for practical memory\r\ngains.
We prove that the resulting approach maintains theoretical convergence\r\nguarantees
competitive to those of AMSGrad, while providing good practical performance. Specifically,
we show that MICROADAM can be implemented efficiently\r\non GPUs: on both million-scale
(BERT) and billion-scale (LLaMA) models, MICROADAM provides practical convergence
competitive to that of the uncompressed\r\nAdam baseline, with lower memory usage
and similar running time. Our code is\r\navailable at https://github.com/IST-DASLab/MicroAdam."
acknowledged_ssus:
- _id: CampIT
acknowledgement: The authors thank Razvan Pascanu, Mahdi Nikdan and Soroush Tabesh
for their valuable feedback, the IT department from Institute of Science and Technology
Austria for the hardware support and Weights and Biases for the infrastructure to
track all our experiments. Mher Safaryan has received funding from the European
Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie
grant agreement No 101034413.
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
author:
- first_name: Ionut-Vlad
full_name: Modoranu, Ionut-Vlad
id: 449f7a18-f128-11eb-9611-9b430c0c6333
last_name: Modoranu
- first_name: Mher
full_name: Safaryan, Mher
id: dd546b39-0804-11ed-9c55-ef075c39778d
last_name: Safaryan
- first_name: Grigory
full_name: Malinovsky, Grigory
last_name: Malinovsky
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Thomas
full_name: Robert, Thomas
id: de632733-1457-11f0-ae22-b5914b8c1c41
last_name: Robert
- first_name: Peter
full_name: Richtárik, Peter
last_name: Richtárik
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Modoranu I-V, Safaryan M, Malinovsky G, et al. MICROADAM: Accurate adaptive
optimization with low space overhead and provable convergence. In: 38th Conference
on Neural Information Processing Systems. Vol 37. Neural Information Processing
Systems Foundation; 2024. doi:10.52202/079017-0001'
apa: 'Modoranu, I.-V., Safaryan, M., Malinovsky, G., Kurtic, E., Robert, T., Richtárik,
P., & Alistarh, D.-A. (2024). MICROADAM: Accurate adaptive optimization with
low space overhead and provable convergence. In 38th Conference on Neural Information
Processing Systems (Vol. 37). Neural Information Processing Systems Foundation.
https://doi.org/10.52202/079017-0001'
chicago: 'Modoranu, Ionut-Vlad, Mher Safaryan, Grigory Malinovsky, Eldar Kurtic,
Thomas Robert, Peter Richtárik, and Dan-Adrian Alistarh. “MICROADAM: Accurate
Adaptive Optimization with Low Space Overhead and Provable Convergence.” In 38th
Conference on Neural Information Processing Systems, Vol. 37. Neural Information
Processing Systems Foundation, 2024. https://doi.org/10.52202/079017-0001.'
ieee: 'I.-V. Modoranu et al., “MICROADAM: Accurate adaptive optimization
with low space overhead and provable convergence,” in 38th Conference on Neural
Information Processing Systems, 2024, vol. 37.'
ista: 'Modoranu I-V, Safaryan M, Malinovsky G, Kurtic E, Robert T, Richtárik P,
Alistarh D-A. 2024. MICROADAM: Accurate adaptive optimization with low space overhead
and provable convergence. 38th Conference on Neural Information Processing Systems.
, Advances in Neural Information Processing Systems, vol. 37.'
mla: 'Modoranu, Ionut-Vlad, et al. “MICROADAM: Accurate Adaptive Optimization with
Low Space Overhead and Provable Convergence.” 38th Conference on Neural Information
Processing Systems, vol. 37, Neural Information Processing Systems Foundation,
2024, doi:10.52202/079017-0001.'
short: I.-V. Modoranu, M. Safaryan, G. Malinovsky, E. Kurtic, T. Robert, P. Richtárik,
D.-A. Alistarh, in:, 38th Conference on Neural Information Processing Systems,
Neural Information Processing Systems Foundation, 2024.
corr_author: '1'
date_created: 2025-04-06T22:01:32Z
date_published: 2024-12-20T00:00:00Z
date_updated: 2026-10-15T09:49:27Z
day: '20'
department:
- _id: DaAl
doi: 10.52202/079017-0001
ec_funded: 1
external_id:
arxiv:
- '2405.15593'
fulldoi: https://doi.org/10.52202/079017-0001
intvolume: ' 37'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2405.15593
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: 38th Conference on Neural Information Processing Systems
publication_identifier:
issn:
- 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/IST-DASLab/MicroAdam
scopus_import: '1'
status: public
title: 'MICROADAM: Accurate adaptive optimization with low space overhead and provable
convergence'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2024'
...