---
_id: '10767'
abstract:
- lang: eng
text: The t-haplotype of mice is a classical model for autosomal transmission distortion.
A largely non-recombining variant of the proximal region of chromosome 17, it
is transmitted to more than 90% of the progeny of heterozygous males through the
disabling of sperm carrying a standard chromosome. While extensive genetic and
functional work has shed light on individual genes involved in drive, much less
is known about the evolution and function of the rest of its hundreds of genes.
Here, we characterize the sequence and expression of dozens of t-specific transcripts
and of their chromosome 17 homologues. Many genes showed reduced expression of
the t-allele, but an equal number of genes showed increased expression of their
t-copy, consistent with increased activity or a newly evolved function. Genes
on the t-haplotype had a significantly higher non-synonymous substitution rate
than their homologues on the standard chromosome, with several genes harbouring
dN/dS ratios above 1. Finally, the t-haplotype has acquired at least two genes
from other chromosomes, which show high and tissue-specific expression. These
results provide a first overview of the gene content of this selfish element,
and support a more dynamic evolutionary scenario than expected of a large genomic
region with almost no recombination.
acknowledgement: "This project has received funding from the European Research Council
under the European Union’s Horizon 2020 research and innovation program (grant agreement
no. 715257) and from the Swiss National Science Foundation (grant no. 310030_189145).\r\nWe
thank Jari Garbely of the Department of Evolutionary Biology and Environmental Studies,
University of Zurich, Zurich, Switzerland, for conducting the PCR verification.
Barbara\r\nKonig, Gabi Stichel and A.K.L. collected mouse tissue samples, from the
field study led by R.K.K. "
article_processing_charge: No
article_type: original
author:
- first_name: Réka K
full_name: Kelemen, Réka K
id: 48D3F8DE-F248-11E8-B48F-1D18A9856A87
last_name: Kelemen
orcid: 0000-0002-8489-9281
- first_name: Marwan N
full_name: Elkrewi, Marwan N
id: 0B46FACA-A8E1-11E9-9BD3-79D1E5697425
last_name: Elkrewi
orcid: 0000-0002-5328-7231
- first_name: Anna K.
full_name: Lindholm, Anna K.
last_name: Lindholm
- first_name: Beatriz
full_name: Vicoso, Beatriz
id: 49E1C5C6-F248-11E8-B48F-1D18A9856A87
last_name: Vicoso
orcid: 0000-0002-4579-8306
citation:
ama: 'Kelemen RK, Elkrewi MN, Lindholm AK, Vicoso B. Novel patterns of expression
and recruitment of new genes on the t-haplotype, a mouse selfish chromosome. Proceedings
of the Royal Society B: Biological Sciences. 2022;289(1968):20211985. doi:10.1098/rspb.2021.1985'
apa: 'Kelemen, R. K., Elkrewi, M. N., Lindholm, A. K., & Vicoso, B. (2022).
Novel patterns of expression and recruitment of new genes on the t-haplotype,
a mouse selfish chromosome. Proceedings of the Royal Society B: Biological
Sciences. The Royal Society. https://doi.org/10.1098/rspb.2021.1985'
chicago: 'Kelemen, Réka K, Marwan N Elkrewi, Anna K. Lindholm, and Beatriz Vicoso.
“Novel Patterns of Expression and Recruitment of New Genes on the T-Haplotype,
a Mouse Selfish Chromosome.” Proceedings of the Royal Society B: Biological
Sciences. The Royal Society, 2022. https://doi.org/10.1098/rspb.2021.1985.'
ieee: 'R. K. Kelemen, M. N. Elkrewi, A. K. Lindholm, and B. Vicoso, “Novel patterns
of expression and recruitment of new genes on the t-haplotype, a mouse selfish
chromosome,” Proceedings of the Royal Society B: Biological Sciences, vol.
289, no. 1968. The Royal Society, p. 20211985, 2022.'
ista: 'Kelemen RK, Elkrewi MN, Lindholm AK, Vicoso B. 2022. Novel patterns of expression
and recruitment of new genes on the t-haplotype, a mouse selfish chromosome. Proceedings
of the Royal Society B: Biological Sciences. 289(1968), 20211985.'
mla: 'Kelemen, Réka K., et al. “Novel Patterns of Expression and Recruitment of
New Genes on the T-Haplotype, a Mouse Selfish Chromosome.” Proceedings of the
Royal Society B: Biological Sciences, vol. 289, no. 1968, The Royal Society,
2022, p. 20211985, doi:10.1098/rspb.2021.1985.'
short: 'R.K. Kelemen, M.N. Elkrewi, A.K. Lindholm, B. Vicoso, Proceedings of the
Royal Society B: Biological Sciences 289 (2022) 20211985.'
corr_author: '1'
date_created: 2022-02-20T23:01:31Z
date_published: 2022-02-09T00:00:00Z
date_updated: 2026-06-19T22:31:10Z
day: '09'
ddc:
- '570'
department:
- _id: BeVi
doi: 10.1098/rspb.2021.1985
ec_funded: 1
external_id:
isi:
- '000752812800012'
pmid:
- '35135349'
file:
- access_level: open_access
checksum: 27042a3706ae52a919fed1ac114bf7bb
content_type: application/pdf
creator: dernst
date_created: 2022-02-21T08:17:38Z
date_updated: 2022-02-21T08:17:38Z
file_id: '10779'
file_name: 2022_ProceedingsRoyalSocB_Kelemen.pdf
file_size: 2366976
relation: main_file
success: 1
file_date_updated: 2022-02-21T08:17:38Z
has_accepted_license: '1'
intvolume: ' 289'
isi: 1
issue: '1968'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: '20211985'
pmid: 1
project:
- _id: 250BDE62-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715257'
name: Prevalence and Influence of Sexual Antagonism on Genome Evolution
publication: 'Proceedings of the Royal Society B: Biological Sciences'
publication_identifier:
eissn:
- 1471-2954
publication_status: published
publisher: The Royal Society
quality_controlled: '1'
related_material:
record:
- id: '17119'
relation: dissertation_contains
status: public
- id: '19386'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Novel patterns of expression and recruitment of new genes on the t-haplotype,
a mouse selfish chromosome
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 289
year: '2022'
...
---
_id: '10924'
abstract:
- lang: eng
text: Solid-state microwave systems offer strong interactions for fast quantum logic
and sensing but photons at telecom wavelength are the ideal choice for high-density
low-loss quantum interconnects. A general-purpose interface that can make use
of single photon effects requires < 1 input noise quanta, which has remained elusive
due to either low efficiency or pump induced heating. Here we demonstrate coherent
electro-optic modulation on nanosecond-timescales with only 0.16+0.02−0.01 microwave
input noise photons with a total bidirectional transduction efficiency of 8.7%
(or up to 15% with 0.41+0.02−0.02), as required for near-term heralded quantum
network protocols. The use of short and high-power optical pump pulses also enables
near-unity cooperativity of the electro-optic interaction leading to an internal
pure conversion efficiency of up to 99.5%. Together with the low mode occupancy
this provides evidence for electro-optic laser cooling and vacuum amplification
as predicted a decade ago.
acknowledged_ssus:
- _id: M-Shop
acknowledgement: "The authors thank S. Wald and F. Diorico for their help with optical
filtering, O. Hosten\r\nand M. Aspelmeyer for equipment, H.G.L. Schwefel for materials
and discussions, L.\r\nDrmic and P. Zielinski for software support, and the MIBA
workshop at IST Austria for\r\nmachining the microwave cavity. This work was supported
by the European Research\r\nCouncil under grant agreement no. 758053 (ERC StG QUNNECT)
and the European\r\nUnion’s Horizon 2020 research and innovation program under grant
agreement no.\r\n899354 (FETopen SuperQuLAN). W.H. is the recipient of an ISTplus
postdoctoral fellowship\r\nwith funding from the European Union’s Horizon 2020 research
and innovation\r\nprogram under the Marie Skłodowska-Curie grant agreement no. 754411.
G.A. is the\r\nrecipient of a DOC fellowship of the Austrian Academy of Sciences
at IST Austria. J.M.F.\r\nacknowledges support from the Austrian Science Fund (FWF)
through BeyondC (F7105)\r\nand the European Union’s Horizon 2020 research and innovation
programs under grant\r\nagreement no. 862644 (FETopen QUARTET)."
article_number: '1276'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Rishabh
full_name: Sahu, Rishabh
id: 47D26E34-F248-11E8-B48F-1D18A9856A87
last_name: Sahu
orcid: 0000-0001-6264-2162
- first_name: William J
full_name: Hease, William J
id: 29705398-F248-11E8-B48F-1D18A9856A87
last_name: Hease
orcid: 0000-0001-9868-2166
- first_name: Alfredo R
full_name: Rueda Sanchez, Alfredo R
id: 3B82B0F8-F248-11E8-B48F-1D18A9856A87
last_name: Rueda Sanchez
orcid: 0000-0001-6249-5860
- first_name: Georg M
full_name: Arnold, Georg M
id: 3770C838-F248-11E8-B48F-1D18A9856A87
last_name: Arnold
orcid: 0000-0003-1397-7876
- first_name: Liu
full_name: Qiu, Liu
id: 45e99c0d-1eb1-11eb-9b96-ed8ab2983cac
last_name: Qiu
orcid: 0000-0003-4345-4267
- first_name: Johannes M
full_name: Fink, Johannes M
id: 4B591CBA-F248-11E8-B48F-1D18A9856A87
last_name: Fink
orcid: 0000-0001-8112-028X
citation:
ama: Sahu R, Hease WJ, Rueda Sanchez AR, Arnold GM, Qiu L, Fink JM. Quantum-enabled
operation of a microwave-optical interface. Nature Communications. 2022;13.
doi:10.1038/s41467-022-28924-2
apa: Sahu, R., Hease, W. J., Rueda Sanchez, A. R., Arnold, G. M., Qiu, L., &
Fink, J. M. (2022). Quantum-enabled operation of a microwave-optical interface.
Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-022-28924-2
chicago: Sahu, Rishabh, William J Hease, Alfredo R Rueda Sanchez, Georg M Arnold,
Liu Qiu, and Johannes M Fink. “Quantum-Enabled Operation of a Microwave-Optical
Interface.” Nature Communications. Springer Nature, 2022. https://doi.org/10.1038/s41467-022-28924-2.
ieee: R. Sahu, W. J. Hease, A. R. Rueda Sanchez, G. M. Arnold, L. Qiu, and J. M.
Fink, “Quantum-enabled operation of a microwave-optical interface,” Nature
Communications, vol. 13. Springer Nature, 2022.
ista: Sahu R, Hease WJ, Rueda Sanchez AR, Arnold GM, Qiu L, Fink JM. 2022. Quantum-enabled
operation of a microwave-optical interface. Nature Communications. 13, 1276.
mla: Sahu, Rishabh, et al. “Quantum-Enabled Operation of a Microwave-Optical Interface.”
Nature Communications, vol. 13, 1276, Springer Nature, 2022, doi:10.1038/s41467-022-28924-2.
short: R. Sahu, W.J. Hease, A.R. Rueda Sanchez, G.M. Arnold, L. Qiu, J.M. Fink,
Nature Communications 13 (2022).
corr_author: '1'
date_created: 2022-03-27T22:01:45Z
date_published: 2022-03-11T00:00:00Z
date_updated: 2026-06-19T22:31:12Z
day: '11'
ddc:
- '530'
department:
- _id: JoFi
doi: 10.1038/s41467-022-28924-2
ec_funded: 1
external_id:
arxiv:
- '2107.08303'
isi:
- '000767892300013'
pmid:
- '35277488'
file:
- access_level: open_access
checksum: 7c5176db7b8e2ed18a4e0c5aca70a72c
content_type: application/pdf
creator: dernst
date_created: 2022-03-28T08:02:12Z
date_updated: 2022-03-28T08:02:12Z
file_id: '10929'
file_name: 2022_NatureCommunications_Sahu.pdf
file_size: 1167492
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success: 1
file_date_updated: 2022-03-28T08:02:12Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 26336814-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '758053'
name: A Fiber Optic Transceiver for Superconducting Qubits
- _id: 9B868D20-BA93-11EA-9121-9846C619BF3A
call_identifier: H2020
grant_number: '899354'
name: Quantum Local Area Networks with Superconducting Qubits
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 237CBA6C-32DE-11EA-91FC-C7463DDC885E
call_identifier: H2020
grant_number: '862644'
name: Quantum readout techniques and technologies
- _id: bdb108fd-d553-11ed-ba76-83dc74a9864f
grant_number: F07105
name: QUANTUM INFORMATION SYSTEMS BEYOND CLASSICAL CAPABILITIES / P5- Integration
of Superconducting Quantum Circuits
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13175'
relation: dissertation_contains
status: public
- id: '12900'
relation: dissertation_contains
status: public
- id: '18871'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Quantum-enabled operation of a microwave-optical interface
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: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2022'
...
---
OA_place: publisher
_id: '11196'
abstract:
- lang: eng
text: "One of the fundamental questions in Neuroscience is how the structure of
synapses and their physiological properties are related. While synaptic transmission
remains a dynamic process, electron microscopy provides images with comparably
low temporal resolution (Studer et al., 2014). The current work overcomes this
challenge and describes an improved “Flash and Freeze” technique (Watanabe et
al., 2013a; Watanabe et al., 2013b) to study synaptic transmission at the hippocampal
mossy fiber-CA3 pyramidal neuron synapses, using mouse acute brain slices and
organotypic slices culture. The improved method allowed for selective stimulation
of presynaptic mossy fiber boutons and the observation of synaptic vesicle pool
dynamics at the active zones. Our results uncovered several intriguing morphological
features of mossy fiber boutons. First, the docked vesicle pool was largely depleted
(more than 70%) after stimulation, implying that the docked synaptic vesicles
pool and readily releasable pool are vastly overlapping in mossy fiber boutons.
Second, the synaptic vesicles are skewed towards larger diameters, displaying
a wide range of sizes. An increase in the mean diameter of synaptic vesicles,
after single and repetitive stimulation, suggests that smaller vesicles have a
higher release probability. Third, we observed putative endocytotic structures
after moderate light stimulation, matching the timing of previously described
ultrafast endocytosis (Watanabe et al., 2013a; Delvendahl et al., 2016). \r\n\tIn
addition, synaptic transmission depends on a sophisticated system of protein machinery
and calcium channels (Südhof, 2013b), which amplifies the challenge in studying
synaptic communication as these interactions can be potentially modified during
synaptic plasticity. And although recent study elucidated the potential correlation
between physiological and morphological properties of synapses during synaptic
plasticity (Vandael et al., 2020), the molecular underpinning of it remains unknown.
Thus, the presented work tries to overcome this challenge and aims to pinpoint
changes in the molecular architecture at hippocampal mossy fiber bouton synapses
during short- and long-term potentiation (STP and LTP), we combined chemical potentiation,
with the application of a cyclic adenosine monophosphate agonist (i.e. forskolin)
and freeze-fracture replica immunolabelling. This method allowed the localization
of membrane-bound proteins with nanometer precision within the active zone, in
particular, P/Q-type calcium channels and synaptic vesicle priming proteins Munc13-1/2.
First, we found that the number of clusters of Munc13-1 in the mossy fiber bouton
active zone increased significantly during STP, but decreased to lower than the
control value during LTP. Secondly, although the distance between the calcium
channels and Munc13-1s did not change after induction of STP, it shortened during
the LTP phase. Additionally, forskolin did not affect Munc13-2 distribution during
STP and LTP. These results indicate the existence of two distinct mechanisms that
govern STP and LTP at mossy fiber bouton synapses: an increase in the readily
realizable pool in the case of STP and a potential increase in release probability
during LTP. “Flash and freeze” and functional electron microscopy, are versatile
methods that can be successfully applied to intact brain circuits to study synaptic
transmission even at the molecular level.\r\n"
acknowledged_ssus:
- _id: EM-Fac
- _id: PreCl
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Olena
full_name: Kim, Olena
id: 3F8ABDDA-F248-11E8-B48F-1D18A9856A87
last_name: Kim
orcid: 0000-0003-2344-1039
citation:
ama: Kim O. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses.
2022. doi:10.15479/at:ista:11196
apa: Kim, O. (2022). Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal
neuron synapses. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:11196
chicago: Kim, Olena. “Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal
Neuron Synapses.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11196.
ieee: O. Kim, “Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron
synapses,” Institute of Science and Technology Austria, 2022.
ista: Kim O. 2022. Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron
synapses. Institute of Science and Technology Austria.
mla: Kim, Olena. Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron
Synapses. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:11196.
short: O. Kim, Nanoarchitecture of Hippocampal Mossy Fiber-CA3 Pyramidal Neuron
Synapses, Institute of Science and Technology Austria, 2022.
corr_author: '1'
date_created: 2022-04-20T09:47:12Z
date_published: 2022-04-20T00:00:00Z
date_updated: 2026-06-18T10:49:27Z
day: '20'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: PeJo
- _id: GradSch
doi: 10.15479/at:ista:11196
ec_funded: 1
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creator: okim
date_created: 2022-04-20T14:21:56Z
date_updated: 2023-04-20T22:30:03Z
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file_name: Olena_KIM_thesis_final.pdf
file_size: 21273537
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language:
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month: '04'
oa: 1
oa_version: Published Version
page: '132'
project:
- _id: 25BAF7B2-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '708497'
name: Presynaptic calcium channels distribution and impact on coupling at the hippocampal
mossy fiber synapse
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '692692'
name: Biophysics and circuit function of a giant cortical glutamatergic synapse
- _id: 25C3DBB6-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: W01205
name: Zellkommunikation in Gesundheit und Krankheit
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00312
name: Synaptic communication in neuronal microcircuits
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7473'
relation: part_of_dissertation
status: public
- id: '11222'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
title: Nanoarchitecture of hippocampal mossy fiber-CA3 pyramidal neuron synapses
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: dissertation
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2022'
...
---
_id: '12272'
abstract:
- lang: eng
text: Reading, interpreting and crawling along gradients of chemotactic cues is
one of the most complex questions in cell biology. In this issue, Georgantzoglou
et al. (2022. J. Cell. Biol.https://doi.org/10.1083/jcb.202103207) use in vivo
models to map the temporal sequence of how neutrophils respond to an acutely arising
gradient of chemoattractant.
article_number: e202206127
article_processing_charge: No
article_type: original
author:
- first_name: Julian A
full_name: Stopp, Julian A
id: 489E3F00-F248-11E8-B48F-1D18A9856A87
last_name: Stopp
- first_name: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-6620-9179
citation:
ama: 'Stopp JA, Sixt MK. Plan your trip before you leave: The neutrophils’ search-and-run
journey. Journal of Cell Biology. 2022;221(8). doi:10.1083/jcb.202206127'
apa: 'Stopp, J. A., & Sixt, M. K. (2022). Plan your trip before you leave: The
neutrophils’ search-and-run journey. Journal of Cell Biology. Rockefeller
University Press. https://doi.org/10.1083/jcb.202206127'
chicago: 'Stopp, Julian A, and Michael K Sixt. “Plan Your Trip before You Leave:
The Neutrophils’ Search-and-Run Journey.” Journal of Cell Biology. Rockefeller
University Press, 2022. https://doi.org/10.1083/jcb.202206127.'
ieee: 'J. A. Stopp and M. K. Sixt, “Plan your trip before you leave: The neutrophils’
search-and-run journey,” Journal of Cell Biology, vol. 221, no. 8. Rockefeller
University Press, 2022.'
ista: 'Stopp JA, Sixt MK. 2022. Plan your trip before you leave: The neutrophils’
search-and-run journey. Journal of Cell Biology. 221(8), e202206127.'
mla: 'Stopp, Julian A., and Michael K. Sixt. “Plan Your Trip before You Leave: The
Neutrophils’ Search-and-Run Journey.” Journal of Cell Biology, vol. 221,
no. 8, e202206127, Rockefeller University Press, 2022, doi:10.1083/jcb.202206127.'
short: J.A. Stopp, M.K. Sixt, Journal of Cell Biology 221 (2022).
corr_author: '1'
date_created: 2023-01-16T10:01:08Z
date_published: 2022-07-20T00:00:00Z
date_updated: 2026-06-19T22:31:20Z
day: '20'
ddc:
- '570'
department:
- _id: MiSi
doi: 10.1083/jcb.202206127
external_id:
isi:
- '000874717200001'
pmid:
- '35856919'
file:
- access_level: open_access
checksum: 6b1620743669679b48b9389bb40f5a11
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T10:39:34Z
date_updated: 2023-01-30T10:39:34Z
file_id: '12451'
file_name: 2022_JourCellBiology_Stopp.pdf
file_size: 969969
relation: main_file
success: 1
file_date_updated: 2023-01-30T10:39:34Z
has_accepted_license: '1'
intvolume: ' 221'
isi: 1
issue: '8'
keyword:
- Cell Biology
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-sa/4.0/
month: '07'
oa: 1
oa_version: Published Version
pmid: 1
publication: Journal of Cell Biology
publication_identifier:
eissn:
- 1540-8140
issn:
- 0021-9525
publication_status: published
publisher: Rockefeller University Press
quality_controlled: '1'
related_material:
record:
- id: '14697'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: 'Plan your trip before you leave: The neutrophils’ search-and-run journey'
tmp:
image: /images/cc_by_nc_sa.png
legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
BY-NC-SA 4.0)
short: CC BY-NC-SA (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 221
year: '2022'
...
---
_id: '11420'
abstract:
- lang: eng
text: 'Understanding the properties of neural networks trained via stochastic gradient
descent (SGD) is at the heart of the theory of deep learning. In this work, we
take a mean-field view, and consider a two-layer ReLU network trained via noisy-SGD
for a univariate regularized regression problem. Our main result is that SGD with
vanishingly small noise injected in the gradients is biased towards a simple solution:
at convergence, the ReLU network implements a piecewise linear map of the inputs,
and the number of “knot” points -- i.e., points where the tangent of the ReLU
network estimator changes -- between two consecutive training inputs is at most
three. In particular, as the number of neurons of the network grows, the SGD dynamics
is captured by the solution of a gradient flow and, at convergence, the distribution
of the weights approaches the unique minimizer of a related free energy, which
has a Gibbs form. Our key technical contribution consists in the analysis of the
estimator resulting from this minimizer: we show that its second derivative vanishes
everywhere, except at some specific locations which represent the “knot” points.
We also provide empirical evidence that knots at locations distinct from the data
points might occur, as predicted by our theory.'
acknowledgement: "We would like to thank Mert Pilanci for several exploratory discussions
in the early stage\r\nof the project, Jan Maas for clarifications about Jordan et
al. (1998), and Max Zimmer for\r\nsuggestive numerical experiments. A. Shevchenko
and M. Mondelli are partially supported\r\nby the 2019 Lopez-Loreta Prize. V. Kungurtsev
acknowledges support to the OP VVV\r\nproject CZ.02.1.01/0.0/0.0/16 019/0000765
Research Center for Informatics.\r\n"
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Aleksandr
full_name: Shevchenko, Aleksandr
id: F2B06EC2-C99E-11E9-89F0-752EE6697425
last_name: Shevchenko
- first_name: Vyacheslav
full_name: Kungurtsev, Vyacheslav
last_name: Kungurtsev
- first_name: Marco
full_name: Mondelli, Marco
id: 27EB676C-8706-11E9-9510-7717E6697425
last_name: Mondelli
orcid: 0000-0002-3242-7020
citation:
ama: Shevchenko A, Kungurtsev V, Mondelli M. Mean-field analysis of piecewise linear
solutions for wide ReLU networks. Journal of Machine Learning Research.
2022;23(130):1-55.
apa: Shevchenko, A., Kungurtsev, V., & Mondelli, M. (2022). Mean-field analysis
of piecewise linear solutions for wide ReLU networks. Journal of Machine Learning
Research. Journal of Machine Learning Research.
chicago: Shevchenko, Alexander, Vyacheslav Kungurtsev, and Marco Mondelli. “Mean-Field
Analysis of Piecewise Linear Solutions for Wide ReLU Networks.” Journal of
Machine Learning Research. Journal of Machine Learning Research, 2022.
ieee: A. Shevchenko, V. Kungurtsev, and M. Mondelli, “Mean-field analysis of piecewise
linear solutions for wide ReLU networks,” Journal of Machine Learning Research,
vol. 23, no. 130. Journal of Machine Learning Research, pp. 1–55, 2022.
ista: Shevchenko A, Kungurtsev V, Mondelli M. 2022. Mean-field analysis of piecewise
linear solutions for wide ReLU networks. Journal of Machine Learning Research.
23(130), 1–55.
mla: Shevchenko, Alexander, et al. “Mean-Field Analysis of Piecewise Linear Solutions
for Wide ReLU Networks.” Journal of Machine Learning Research, vol. 23,
no. 130, Journal of Machine Learning Research, 2022, pp. 1–55.
short: A. Shevchenko, V. Kungurtsev, M. Mondelli, Journal of Machine Learning Research
23 (2022) 1–55.
corr_author: '1'
date_created: 2022-05-29T22:01:54Z
date_published: 2022-04-01T00:00:00Z
date_updated: 2026-06-19T22:31:21Z
day: '01'
ddc:
- '000'
department:
- _id: MaMo
- _id: DaAl
external_id:
arxiv:
- '2111.02278'
file:
- access_level: open_access
checksum: d4ff5d1affb34848b5c5e4002483fc62
content_type: application/pdf
creator: cchlebak
date_created: 2022-05-30T08:22:55Z
date_updated: 2022-05-30T08:22:55Z
file_id: '11422'
file_name: 21-1365.pdf
file_size: 1521701
relation: main_file
success: 1
file_date_updated: 2022-05-30T08:22:55Z
has_accepted_license: '1'
intvolume: ' 23'
issue: '130'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 1-55
project:
- _id: 059876FA-7A3F-11EA-A408-12923DDC885E
name: Prix Lopez-Loretta 2019 - Marco Mondelli
publication: Journal of Machine Learning Research
publication_identifier:
eissn:
- 1533-7928
issn:
- 1532-4435
publication_status: published
publisher: Journal of Machine Learning Research
quality_controlled: '1'
related_material:
link:
- relation: other
url: https://www.jmlr.org/papers/v23/21-1365.html
record:
- id: '17465'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Mean-field analysis of piecewise linear solutions for wide ReLU networks
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: 8b945eb4-e2f2-11eb-945a-df72226e66a9
volume: 23
year: '2022'
...
---
_id: '12186'
abstract:
- lang: eng
text: Activation of cell-surface and intracellular receptor-mediated immunity results
in rapid transcriptional reprogramming that underpins disease resistance. However,
the mechanisms by which co-activation of both immune systems lead to transcriptional
changes are not clear. Here, we combine RNA-seq and ATAC-seq to define changes
in gene expression and chromatin accessibility. Activation of cell-surface or
intracellular receptor-mediated immunity, or both, increases chromatin accessibility
at induced defence genes. Analysis of ATAC-seq and RNA-seq data combined with
publicly available information on transcription factor DNA-binding motifs enabled
comparison of individual gene regulatory networks activated by cell-surface or
intracellular receptor-mediated immunity, or by both. These results and analyses
reveal overlapping and conserved transcriptional regulatory mechanisms between
the two immune systems.
acknowledgement: "We thank the Gatsby Foundation (UK) for funding to the JDGJ laboratory.
PD acknowledges support from the European Union’s Horizon 2020 Research and Innovation
Program under Marie Skłodowska Curie Actions (grant agreement: 656243) and a Future
Leader Fellowship from the Biotechnology and Biological Sciences Research Council
(BBSRC) (grant agreement: BB/R012172/1). TS, RKS, DM, and JDGJ were supported by
the Gatsby Foundation funding to the\r\nSainsbury Laboratory. NMP and KV were supported
by a BOF grant from Ghent University (grant agreement: BOF24Y2019001901). WG and
RZ were supported by the Scottish Government Rural and Environment Science and Analytical
Services division (RESAS), and RZ also acknowledges the support from a BBSRC Bioinformatics
and Biological Resources Fund (grant agreement: BB/S020160/1).BPMN was supported
by the Norwich Research Park (NRP) Biosciences Doctoral Training Partnership (DTP)
funded by the BBSRC (grant agreement: BB/M011216/1). SH and XF were supported by
a BBSRC Responsive Mode grant (grant agreement: BB/S009620/1) and a European Research
Council Starting grant ‘SexMeth’ (grant agreement: 804981). CL was supported by
Deutsche Forschungsgemeinschaft (grant agreement: LI 2862/4). "
article_processing_charge: No
article_type: original
author:
- first_name: Pingtao
full_name: Ding, Pingtao
last_name: Ding
- first_name: Toshiyuki
full_name: Sakai, Toshiyuki
last_name: Sakai
- first_name: Ram
full_name: Krishna Shrestha, Ram
last_name: Krishna Shrestha
- first_name: Nicolas
full_name: Manosalva Perez, Nicolas
last_name: Manosalva Perez
- first_name: Wenbin
full_name: Guo, Wenbin
last_name: Guo
- first_name: Bruno Pok Man
full_name: Ngou, Bruno Pok Man
last_name: Ngou
- first_name: Shengbo
full_name: He, Shengbo
last_name: He
- first_name: Chang
full_name: Liu, Chang
last_name: Liu
- first_name: Xiaoqi
full_name: Feng, Xiaoqi
id: e0164712-22ee-11ed-b12a-d80fcdf35958
last_name: Feng
orcid: 0000-0002-4008-1234
- first_name: Runxuan
full_name: Zhang, Runxuan
last_name: Zhang
- first_name: Klaas
full_name: Vandepoele, Klaas
last_name: Vandepoele
- first_name: Dan
full_name: MacLean, Dan
last_name: MacLean
- first_name: Jonathan D G
full_name: Jones, Jonathan D G
last_name: Jones
citation:
ama: Ding P, Sakai T, Krishna Shrestha R, et al. Chromatin accessibility landscapes
activated by cell-surface and intracellular immune receptors. Journal of Experimental
Botany. 2021;72(22):7927-7941. doi:10.1093/jxb/erab373
apa: Ding, P., Sakai, T., Krishna Shrestha, R., Manosalva Perez, N., Guo, W., Ngou,
B. P. M., … Jones, J. D. G. (2021). Chromatin accessibility landscapes activated
by cell-surface and intracellular immune receptors. Journal of Experimental
Botany. Oxford University Press. https://doi.org/10.1093/jxb/erab373
chicago: Ding, Pingtao, Toshiyuki Sakai, Ram Krishna Shrestha, Nicolas Manosalva
Perez, Wenbin Guo, Bruno Pok Man Ngou, Shengbo He, et al. “Chromatin Accessibility
Landscapes Activated by Cell-Surface and Intracellular Immune Receptors.” Journal
of Experimental Botany. Oxford University Press, 2021. https://doi.org/10.1093/jxb/erab373.
ieee: P. Ding et al., “Chromatin accessibility landscapes activated by cell-surface
and intracellular immune receptors,” Journal of Experimental Botany, vol.
72, no. 22. Oxford University Press, pp. 7927–7941, 2021.
ista: Ding P, Sakai T, Krishna Shrestha R, Manosalva Perez N, Guo W, Ngou BPM, He
S, Liu C, Feng X, Zhang R, Vandepoele K, MacLean D, Jones JDG. 2021. Chromatin
accessibility landscapes activated by cell-surface and intracellular immune receptors.
Journal of Experimental Botany. 72(22), 7927–7941.
mla: Ding, Pingtao, et al. “Chromatin Accessibility Landscapes Activated by Cell-Surface
and Intracellular Immune Receptors.” Journal of Experimental Botany, vol.
72, no. 22, Oxford University Press, 2021, pp. 7927–41, doi:10.1093/jxb/erab373.
short: P. Ding, T. Sakai, R. Krishna Shrestha, N. Manosalva Perez, W. Guo, B.P.M.
Ngou, S. He, C. Liu, X. Feng, R. Zhang, K. Vandepoele, D. MacLean, J.D.G. Jones,
Journal of Experimental Botany 72 (2021) 7927–7941.
date_created: 2023-01-16T09:14:35Z
date_published: 2021-08-13T00:00:00Z
date_updated: 2023-05-08T11:01:18Z
day: '13'
department:
- _id: XiFe
doi: 10.1093/jxb/erab373
extern: '1'
external_id:
pmid:
- '34387350'
intvolume: ' 72'
issue: '22'
keyword:
- Plant Science
- Physiology
language:
- iso: eng
month: '08'
oa_version: None
page: 7927-7941
pmid: 1
publication: Journal of Experimental Botany
publication_identifier:
issn:
- 0022-0957
- 1460-2431
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Chromatin accessibility landscapes activated by cell-surface and intracellular
immune receptors
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 72
year: '2021'
...
---
_id: '14117'
abstract:
- lang: eng
text: 'The two fields of machine learning and graphical causality arose and are
developed separately. However, there is, now, cross-pollination and increasing
interest in both fields to benefit from the advances of the other. In this article,
we review fundamental concepts of causal inference and relate them to crucial
open problems of machine learning, including transfer and generalization, thereby
assaying how causality can contribute to modern machine learning research. This
also applies in the opposite direction: we note that most work in causality starts
from the premise that the causal variables are given. A central problem for AI
and causality is, thus, causal representation learning, that is, the discovery
of high-level causal variables from low-level observations. Finally, we delineate
some implications of causality for machine learning and propose key research areas
at the intersection of both communities.'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Bernhard
full_name: Scholkopf, Bernhard
last_name: Scholkopf
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
- first_name: Nan Rosemary
full_name: Ke, Nan Rosemary
last_name: Ke
- first_name: Nal
full_name: Kalchbrenner, Nal
last_name: Kalchbrenner
- first_name: Anirudh
full_name: Goyal, Anirudh
last_name: Goyal
- first_name: Yoshua
full_name: Bengio, Yoshua
last_name: Bengio
citation:
ama: Scholkopf B, Locatello F, Bauer S, et al. Toward causal representation learning.
Proceedings of the IEEE. 2021;109(5):612-634. doi:10.1109/jproc.2021.3058954
apa: Scholkopf, B., Locatello, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal,
A., & Bengio, Y. (2021). Toward causal representation learning. Proceedings
of the IEEE. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/jproc.2021.3058954
chicago: Scholkopf, Bernhard, Francesco Locatello, Stefan Bauer, Nan Rosemary Ke,
Nal Kalchbrenner, Anirudh Goyal, and Yoshua Bengio. “Toward Causal Representation
Learning.” Proceedings of the IEEE. Institute of Electrical and Electronics
Engineers, 2021. https://doi.org/10.1109/jproc.2021.3058954.
ieee: B. Scholkopf et al., “Toward causal representation learning,” Proceedings
of the IEEE, vol. 109, no. 5. Institute of Electrical and Electronics Engineers,
pp. 612–634, 2021.
ista: Scholkopf B, Locatello F, Bauer S, Ke NR, Kalchbrenner N, Goyal A, Bengio
Y. 2021. Toward causal representation learning. Proceedings of the IEEE. 109(5),
612–634.
mla: Scholkopf, Bernhard, et al. “Toward Causal Representation Learning.” Proceedings
of the IEEE, vol. 109, no. 5, Institute of Electrical and Electronics Engineers,
2021, pp. 612–34, doi:10.1109/jproc.2021.3058954.
short: B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal,
Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.
date_created: 2023-08-21T12:19:30Z
date_published: 2021-05-01T00:00:00Z
date_updated: 2023-09-11T11:43:35Z
day: '01'
department:
- _id: FrLo
doi: 10.1109/jproc.2021.3058954
extern: '1'
external_id:
arxiv:
- '2102.11107'
intvolume: ' 109'
issue: '5'
keyword:
- Electrical and Electronic Engineering
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1109/JPROC.2021.3058954
month: '05'
oa: 1
oa_version: Published Version
page: 612-634
publication: Proceedings of the IEEE
publication_identifier:
eissn:
- 1558-2256
issn:
- 0018-9219
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Toward causal representation learning
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 109
year: '2021'
...
---
_id: '14176'
abstract:
- lang: eng
text: "Intensive care units (ICU) are increasingly looking towards machine learning
for methods to provide online monitoring of critically ill patients. In machine
learning, online monitoring is often formulated as a supervised learning problem.
Recently, contrastive learning approaches have demonstrated promising improvements
over competitive supervised benchmarks. These methods rely on well-understood
data augmentation techniques developed for image data which do not apply to online
monitoring. In this work, we overcome this limitation by\r\nsupplementing time-series
data augmentation techniques with a novel contrastive\r\nlearning objective which
we call neighborhood contrastive learning (NCL). Our objective explicitly groups
together contiguous time segments from each patient while maintaining state-specific
information. Our experiments demonstrate a marked improvement over existing work
applying contrastive methods to medical time-series."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Hugo
full_name: Yèche, Hugo
last_name: Yèche
- first_name: Gideon
full_name: Dresdner, Gideon
last_name: Dresdner
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Matthias
full_name: Hüser, Matthias
last_name: Hüser
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
citation:
ama: 'Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. Neighborhood contrastive
learning applied to online patient monitoring. In: Proceedings of 38th International
Conference on Machine Learning. Vol 139. ML Research Press; 2021:11964-11974.'
apa: 'Yèche, H., Dresdner, G., Locatello, F., Hüser, M., & Rätsch, G. (2021).
Neighborhood contrastive learning applied to online patient monitoring. In Proceedings
of 38th International Conference on Machine Learning (Vol. 139, pp. 11964–11974).
Virtual: ML Research Press.'
chicago: Yèche, Hugo, Gideon Dresdner, Francesco Locatello, Matthias Hüser, and
Gunnar Rätsch. “Neighborhood Contrastive Learning Applied to Online Patient Monitoring.”
In Proceedings of 38th International Conference on Machine Learning, 139:11964–74.
ML Research Press, 2021.
ieee: H. Yèche, G. Dresdner, F. Locatello, M. Hüser, and G. Rätsch, “Neighborhood
contrastive learning applied to online patient monitoring,” in Proceedings
of 38th International Conference on Machine Learning, Virtual, 2021, vol.
139, pp. 11964–11974.
ista: Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. 2021. Neighborhood contrastive
learning applied to online patient monitoring. Proceedings of 38th International
Conference on Machine Learning. International Conference on Machine Learning,
PMLR, vol. 139, 11964–11974.
mla: Yèche, Hugo, et al. “Neighborhood Contrastive Learning Applied to Online Patient
Monitoring.” Proceedings of 38th International Conference on Machine Learning,
vol. 139, ML Research Press, 2021, pp. 11964–74.
short: H. Yèche, G. Dresdner, F. Locatello, M. Hüser, G. Rätsch, in:, Proceedings
of 38th International Conference on Machine Learning, ML Research Press, 2021,
pp. 11964–11974.
conference:
end_date: 2021-07-24
location: Virtual
name: International Conference on Machine Learning
start_date: 2021-07-18
date_created: 2023-08-22T14:03:04Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2023-09-11T10:16:55Z
day: '01'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2106.05142'
intvolume: ' 139'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2106.05142
month: '08'
oa: 1
oa_version: Preprint
page: 11964-11974
publication: Proceedings of 38th International Conference on Machine Learning
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Neighborhood contrastive learning applied to online patient monitoring
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 139
year: '2021'
...
---
_id: '14177'
abstract:
- lang: eng
text: "The focus of disentanglement approaches has been on identifying independent
factors of variation in data. However, the causal variables underlying real-world
observations are often not statistically independent. In this work, we bridge
the gap to real-world scenarios by analyzing the behavior of the most prominent
disentanglement approaches on correlated data in a large-scale empirical study
(including 4260 models). We show and quantify that systematically induced correlations
in the dataset are being learned and reflected in the latent representations,
which has implications for downstream applications of disentanglement such as
fairness. We also demonstrate how to resolve these latent correlations, either
using weak supervision during\r\ntraining or by post-hoc correcting a pre-trained
model with a small number of labels."
alternative_title:
- PMLR
article_processing_charge: No
arxiv: 1
author:
- first_name: Frederik
full_name: Träuble, Frederik
last_name: Träuble
- first_name: Elliot
full_name: Creager, Elliot
last_name: Creager
- first_name: Niki
full_name: Kilbertus, Niki
last_name: Kilbertus
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Andrea
full_name: Dittadi, Andrea
last_name: Dittadi
- first_name: Anirudh
full_name: Goyal, Anirudh
last_name: Goyal
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
citation:
ama: 'Träuble F, Creager E, Kilbertus N, et al. On disentangled representations
learned from correlated data. In: Proceedings of the 38th International Conference
on Machine Learning. Vol 139. ML Research Press; 2021:10401-10412.'
apa: 'Träuble, F., Creager, E., Kilbertus, N., Locatello, F., Dittadi, A., Goyal,
A., … Bauer, S. (2021). On disentangled representations learned from correlated
data. In Proceedings of the 38th International Conference on Machine Learning
(Vol. 139, pp. 10401–10412). Virtual: ML Research Press.'
chicago: Träuble, Frederik, Elliot Creager, Niki Kilbertus, Francesco Locatello,
Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, and Stefan Bauer. “On Disentangled
Representations Learned from Correlated Data.” In Proceedings of the 38th International
Conference on Machine Learning, 139:10401–12. ML Research Press, 2021.
ieee: F. Träuble et al., “On disentangled representations learned from correlated
data,” in Proceedings of the 38th International Conference on Machine Learning,
Virtual, 2021, vol. 139, pp. 10401–10412.
ista: 'Träuble F, Creager E, Kilbertus N, Locatello F, Dittadi A, Goyal A, Schölkopf
B, Bauer S. 2021. On disentangled representations learned from correlated data.
Proceedings of the 38th International Conference on Machine Learning. ICML: International
Conference on Machine Learning, PMLR, vol. 139, 10401–10412.'
mla: Träuble, Frederik, et al. “On Disentangled Representations Learned from Correlated
Data.” Proceedings of the 38th International Conference on Machine Learning,
vol. 139, ML Research Press, 2021, pp. 10401–12.
short: F. Träuble, E. Creager, N. Kilbertus, F. Locatello, A. Dittadi, A. Goyal,
B. Schölkopf, S. Bauer, in:, Proceedings of the 38th International Conference
on Machine Learning, ML Research Press, 2021, pp. 10401–10412.
conference:
end_date: 2021-07-24
location: Virtual
name: 'ICML: International Conference on Machine Learning'
start_date: 2021-07-18
date_created: 2023-08-22T14:03:47Z
date_published: 2021-08-01T00:00:00Z
date_updated: 2023-09-11T10:18:48Z
day: '01'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2006.07886'
intvolume: ' 139'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2006.07886
month: '08'
oa: 1
oa_version: Published Version
page: 10401-10412
publication: Proceedings of the 38th International Conference on Machine Learning
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: On disentangled representations learned from correlated data
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 139
year: '2021'
...
---
_id: '14178'
abstract:
- lang: eng
text: Learning meaningful representations that disentangle the underlying structure
of the data generating process is considered to be of key importance in machine
learning. While disentangled representations were found to be useful for diverse
tasks such as abstract reasoning and fair classification, their scalability and
real-world impact remain questionable. We introduce a new high-resolution dataset
with 1M simulated images and over 1,800 annotated real-world images of the same
setup. In contrast to previous work, this new dataset exhibits correlations, a
complex underlying structure, and allows to evaluate transfer to unseen simulated
and real-world settings where the encoder i) remains in distribution or ii) is
out of distribution. We propose new architectures in order to scale disentangled
representation learning to realistic high-resolution settings and conduct a large-scale
empirical study of disentangled representations on this dataset. We observe that
disentanglement is a good predictor for out-of-distribution (OOD) task performance.
article_processing_charge: No
arxiv: 1
author:
- first_name: Andrea
full_name: Dittadi, Andrea
last_name: Dittadi
- first_name: Frederik
full_name: Träuble, Frederik
last_name: Träuble
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Manuel
full_name: Wüthrich, Manuel
last_name: Wüthrich
- first_name: Vaibhav
full_name: Agrawal, Vaibhav
last_name: Agrawal
- first_name: Ole
full_name: Winther, Ole
last_name: Winther
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
citation:
ama: 'Dittadi A, Träuble F, Locatello F, et al. On the transfer of disentangled
representations in realistic settings. In: The Ninth International Conference
on Learning Representations. ; 2021.'
apa: Dittadi, A., Träuble, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther,
O., … Schölkopf, B. (2021). On the transfer of disentangled representations in
realistic settings. In The Ninth International Conference on Learning Representations.
Virtual.
chicago: Dittadi, Andrea, Frederik Träuble, Francesco Locatello, Manuel Wüthrich,
Vaibhav Agrawal, Ole Winther, Stefan Bauer, and Bernhard Schölkopf. “On the Transfer
of Disentangled Representations in Realistic Settings.” In The Ninth International
Conference on Learning Representations, 2021.
ieee: A. Dittadi et al., “On the transfer of disentangled representations
in realistic settings,” in The Ninth International Conference on Learning Representations,
Virtual, 2021.
ista: 'Dittadi A, Träuble F, Locatello F, Wüthrich M, Agrawal V, Winther O, Bauer
S, Schölkopf B. 2021. On the transfer of disentangled representations in realistic
settings. The Ninth International Conference on Learning Representations. ICLR:
International Conference on Learning Representations.'
mla: Dittadi, Andrea, et al. “On the Transfer of Disentangled Representations in
Realistic Settings.” The Ninth International Conference on Learning Representations,
2021.
short: A. Dittadi, F. Träuble, F. Locatello, M. Wüthrich, V. Agrawal, O. Winther,
S. Bauer, B. Schölkopf, in:, The Ninth International Conference on Learning Representations,
2021.
conference:
end_date: 2021-05-07
location: Virtual
name: 'ICLR: International Conference on Learning Representations'
start_date: 2021-05-03
date_created: 2023-08-22T14:04:16Z
date_published: 2021-05-04T00:00:00Z
date_updated: 2023-09-11T10:55:30Z
day: '04'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2010.14407'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2010.14407
month: '05'
oa: 1
oa_version: Preprint
publication: The Ninth International Conference on Learning Representations
publication_status: published
quality_controlled: '1'
status: public
title: On the transfer of disentangled representations in realistic settings
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '14179'
abstract:
- lang: eng
text: Self-supervised representation learning has shown remarkable success in a
number of domains. A common practice is to perform data augmentation via hand-crafted
transformations intended to leave the semantics of the data invariant. We seek
to understand the empirical success of this approach from a theoretical perspective.
We formulate the augmentation process as a latent variable model by postulating
a partition of the latent representation into a content component, which is assumed
invariant to augmentation, and a style component, which is allowed to change.
Unlike prior work on disentanglement and independent component analysis, we allow
for both nontrivial statistical and causal dependencies in the latent space. We
study the identifiability of the latent representation based on pairs of views
of the observations and prove sufficient conditions that allow us to identify
the invariant content partition up to an invertible mapping in both generative
and discriminative settings. We find numerical simulations with dependent latent
variables are consistent with our theory. Lastly, we introduce Causal3DIdent,
a dataset of high-dimensional, visually complex images with rich causal dependencies,
which we use to study the effect of data augmentations performed in practice.
article_processing_charge: No
arxiv: 1
author:
- first_name: Julius von
full_name: Kügelgen, Julius von
last_name: Kügelgen
- first_name: Yash
full_name: Sharma, Yash
last_name: Sharma
- first_name: Luigi
full_name: Gresele, Luigi
last_name: Gresele
- first_name: Wieland
full_name: Brendel, Wieland
last_name: Brendel
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Michel
full_name: Besserve, Michel
last_name: Besserve
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: 'Kügelgen J von, Sharma Y, Gresele L, et al. Self-supervised learning with
data augmentations provably isolates content from style. In: Advances in Neural
Information Processing Systems. Vol 34. ; 2021:16451-16467.'
apa: Kügelgen, J. von, Sharma, Y., Gresele, L., Brendel, W., Schölkopf, B., Besserve,
M., & Locatello, F. (2021). Self-supervised learning with data augmentations
provably isolates content from style. In Advances in Neural Information Processing
Systems (Vol. 34, pp. 16451–16467). Virtual.
chicago: Kügelgen, Julius von, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard
Schölkopf, Michel Besserve, and Francesco Locatello. “Self-Supervised Learning
with Data Augmentations Provably Isolates Content from Style.” In Advances
in Neural Information Processing Systems, 34:16451–67, 2021.
ieee: J. von Kügelgen et al., “Self-supervised learning with data augmentations
provably isolates content from style,” in Advances in Neural Information Processing
Systems, Virtual, 2021, vol. 34, pp. 16451–16467.
ista: 'Kügelgen J von, Sharma Y, Gresele L, Brendel W, Schölkopf B, Besserve M,
Locatello F. 2021. Self-supervised learning with data augmentations provably isolates
content from style. Advances in Neural Information Processing Systems. NeurIPS:
Neural Information Processing Systems vol. 34, 16451–16467.'
mla: Kügelgen, Julius von, et al. “Self-Supervised Learning with Data Augmentations
Provably Isolates Content from Style.” Advances in Neural Information Processing
Systems, vol. 34, 2021, pp. 16451–67.
short: J. von Kügelgen, Y. Sharma, L. Gresele, W. Brendel, B. Schölkopf, M. Besserve,
F. Locatello, in:, Advances in Neural Information Processing Systems, 2021, pp.
16451–16467.
conference:
end_date: 2021-12-10
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-07
date_created: 2023-08-22T14:04:36Z
date_published: 2021-06-08T00:00:00Z
date_updated: 2023-09-11T10:33:19Z
day: '08'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2106.04619'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2106.04619
month: '06'
oa: 1
oa_version: Preprint
page: 16451-16467
publication: Advances in Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
publication_status: published
quality_controlled: '1'
status: public
title: Self-supervised learning with data augmentations provably isolates content
from style
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '14180'
abstract:
- lang: eng
text: 'Modern neural network architectures can leverage large amounts of data to
generalize well within the training distribution. However, they are less capable
of systematic generalization to data drawn from unseen but related distributions,
a feat that is hypothesized to require compositional reasoning and reuse of knowledge.
In this work, we present Neural Interpreters, an architecture that factorizes
inference in a self-attention network as a system of modules, which we call \emph{functions}.
Inputs to the model are routed through a sequence of functions in a way that is
end-to-end learned. The proposed architecture can flexibly compose computation
along width and depth, and lends itself well to capacity extension after training.
To demonstrate the versatility of Neural Interpreters, we evaluate it in two distinct
settings: image classification and visual abstract reasoning on Raven Progressive
Matrices. In the former, we show that Neural Interpreters perform on par with
the vision transformer using fewer parameters, while being transferrable to a
new task in a sample efficient manner. In the latter, we find that Neural Interpreters
are competitive with respect to the state-of-the-art in terms of systematic generalization. '
article_processing_charge: No
arxiv: 1
author:
- first_name: Nasim
full_name: Rahaman, Nasim
last_name: Rahaman
- first_name: Muhammad Waleed
full_name: Gondal, Muhammad Waleed
last_name: Gondal
- first_name: Shruti
full_name: Joshi, Shruti
last_name: Joshi
- first_name: Peter
full_name: Gehler, Peter
last_name: Gehler
- first_name: Yoshua
full_name: Bengio, Yoshua
last_name: Bengio
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
citation:
ama: 'Rahaman N, Gondal MW, Joshi S, et al. Dynamic inference with neural interpreters.
In: Advances in Neural Information Processing Systems. Vol 34. ; 2021:10985-10998.'
apa: Rahaman, N., Gondal, M. W., Joshi, S., Gehler, P., Bengio, Y., Locatello, F.,
& Schölkopf, B. (2021). Dynamic inference with neural interpreters. In Advances
in Neural Information Processing Systems (Vol. 34, pp. 10985–10998). Virtual.
chicago: Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua
Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural
Interpreters.” In Advances in Neural Information Processing Systems, 34:10985–98,
2021.
ieee: N. Rahaman et al., “Dynamic inference with neural interpreters,” in
Advances in Neural Information Processing Systems, Virtual, 2021, vol.
34, pp. 10985–10998.
ista: 'Rahaman N, Gondal MW, Joshi S, Gehler P, Bengio Y, Locatello F, Schölkopf
B. 2021. Dynamic inference with neural interpreters. Advances in Neural Information
Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 10985–10998.'
mla: Rahaman, Nasim, et al. “Dynamic Inference with Neural Interpreters.” Advances
in Neural Information Processing Systems, vol. 34, 2021, pp. 10985–98.
short: N. Rahaman, M.W. Gondal, S. Joshi, P. Gehler, Y. Bengio, F. Locatello, B.
Schölkopf, in:, Advances in Neural Information Processing Systems, 2021, pp. 10985–10998.
conference:
end_date: 2021-12-10
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-07
date_created: 2023-08-22T14:04:55Z
date_published: 2021-10-12T00:00:00Z
date_updated: 2024-10-14T12:27:25Z
day: '12'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2110.06399'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2110.06399
month: '10'
oa: 1
oa_version: Preprint
page: 10985-10998
publication: Advances in Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
publication_status: published
quality_controlled: '1'
status: public
title: Dynamic inference with neural interpreters
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
_id: '14181'
abstract:
- lang: eng
text: Variational Inference makes a trade-off between the capacity of the variational
family and the tractability of finding an approximate posterior distribution.
Instead, Boosting Variational Inference allows practitioners to obtain increasingly
good posterior approximations by spending more compute. The main obstacle to widespread
adoption of Boosting Variational Inference is the amount of resources necessary
to improve over a strong Variational Inference baseline. In our work, we trace
this limitation back to the global curvature of the KL-divergence. We characterize
how the global curvature impacts time and memory consumption, address the problem
with the notion of local curvature, and provide a novel approximate backtracking
algorithm for estimating local curvature. We give new theoretical convergence
rates for our algorithms and provide experimental validation on synthetic and
real-world datasets.
article_processing_charge: No
arxiv: 1
author:
- first_name: Gideon
full_name: Dresdner, Gideon
last_name: Dresdner
- first_name: Saurav
full_name: Shekhar, Saurav
last_name: Shekhar
- first_name: Fabian
full_name: Pedregosa, Fabian
last_name: Pedregosa
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
citation:
ama: 'Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. Boosting variational
inference with locally adaptive step-sizes. In: Proceedings of the Thirtieth
International Joint Conference on Artificial Intelligence. International Joint
Conferences on Artificial Intelligence; 2021:2337-2343. doi:10.24963/ijcai.2021/322'
apa: 'Dresdner, G., Shekhar, S., Pedregosa, F., Locatello, F., & Rätsch, G.
(2021). Boosting variational inference with locally adaptive step-sizes. In Proceedings
of the Thirtieth International Joint Conference on Artificial Intelligence
(pp. 2337–2343). Montreal, Canada: International Joint Conferences on Artificial
Intelligence. https://doi.org/10.24963/ijcai.2021/322'
chicago: Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello,
and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.”
In Proceedings of the Thirtieth International Joint Conference on Artificial
Intelligence, 2337–43. International Joint Conferences on Artificial Intelligence,
2021. https://doi.org/10.24963/ijcai.2021/322.
ieee: G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, and G. Rätsch, “Boosting
variational inference with locally adaptive step-sizes,” in Proceedings of
the Thirtieth International Joint Conference on Artificial Intelligence, Montreal,
Canada, 2021, pp. 2337–2343.
ista: 'Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. 2021. Boosting
variational inference with locally adaptive step-sizes. Proceedings of the Thirtieth
International Joint Conference on Artificial Intelligence. IJCAI: International
Joint Conference on Artificial Intelligence, 2337–2343.'
mla: Dresdner, Gideon, et al. “Boosting Variational Inference with Locally Adaptive
Step-Sizes.” Proceedings of the Thirtieth International Joint Conference on
Artificial Intelligence, International Joint Conferences on Artificial Intelligence,
2021, pp. 2337–43, doi:10.24963/ijcai.2021/322.
short: G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, G. Rätsch, in:, Proceedings
of the Thirtieth International Joint Conference on Artificial Intelligence, International
Joint Conferences on Artificial Intelligence, 2021, pp. 2337–2343.
conference:
end_date: 2021-08-27
location: Montreal, Canada
name: 'IJCAI: International Joint Conference on Artificial Intelligence'
start_date: 2021-08-19
date_created: 2023-08-22T14:05:14Z
date_published: 2021-05-19T00:00:00Z
date_updated: 2023-09-11T11:14:30Z
day: '19'
department:
- _id: FrLo
doi: 10.24963/ijcai.2021/322
extern: '1'
external_id:
arxiv:
- '2105.09240'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2105.09240
month: '05'
oa: 1
oa_version: Published Version
page: 2337-2343
publication: Proceedings of the Thirtieth International Joint Conference on Artificial
Intelligence
publication_identifier:
eisbn:
- '9780999241196'
publication_status: published
publisher: International Joint Conferences on Artificial Intelligence
quality_controlled: '1'
status: public
title: Boosting variational inference with locally adaptive step-sizes
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '14182'
abstract:
- lang: eng
text: "When machine learning systems meet real world applications, accuracy is only\r\none
of several requirements. In this paper, we assay a complementary\r\nperspective
originating from the increasing availability of pre-trained and\r\nregularly improving
state-of-the-art models. While new improved models develop\r\nat a fast pace,
downstream tasks vary more slowly or stay constant. Assume that\r\nwe have a large
unlabelled data set for which we want to maintain accurate\r\npredictions. Whenever
a new and presumably better ML models becomes available,\r\nwe encounter two problems:
(i) given a limited budget, which data points should\r\nbe re-evaluated using
the new model?; and (ii) if the new predictions differ\r\nfrom the current ones,
should we update? Problem (i) is about compute cost,\r\nwhich matters for very
large data sets and models. Problem (ii) is about\r\nmaintaining consistency of
the predictions, which can be highly relevant for\r\ndownstream applications;
our demand is to avoid negative flips, i.e., changing\r\ncorrect to incorrect
predictions. In this paper, we formalize the Prediction\r\nUpdate Problem and
present an efficient probabilistic approach as answer to the\r\nabove questions.
In extensive experiments on standard classification benchmark\r\ndata sets, we
show that our method outperforms alternative strategies along key\r\nmetrics for
backward-compatible prediction updates."
article_processing_charge: No
arxiv: 1
author:
- first_name: Frederik
full_name: Träuble, Frederik
last_name: Träuble
- first_name: Julius von
full_name: Kügelgen, Julius von
last_name: Kügelgen
- first_name: Matthäus
full_name: Kleindessner, Matthäus
last_name: Kleindessner
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Peter
full_name: Gehler, Peter
last_name: Gehler
citation:
ama: 'Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler
P. Backward-compatible prediction updates: A probabilistic approach. In: 35th
Conference on Neural Information Processing Systems. Vol 34. ; 2021:116-128.'
apa: 'Träuble, F., Kügelgen, J. von, Kleindessner, M., Locatello, F., Schölkopf,
B., & Gehler, P. (2021). Backward-compatible prediction updates: A probabilistic
approach. In 35th Conference on Neural Information Processing Systems (Vol.
34, pp. 116–128). Virtual.'
chicago: 'Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco
Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction
Updates: A Probabilistic Approach.” In 35th Conference on Neural Information
Processing Systems, 34:116–28, 2021.'
ieee: 'F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf,
and P. Gehler, “Backward-compatible prediction updates: A probabilistic approach,”
in 35th Conference on Neural Information Processing Systems, Virtual, 2021,
vol. 34, pp. 116–128.'
ista: 'Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler
P. 2021. Backward-compatible prediction updates: A probabilistic approach. 35th
Conference on Neural Information Processing Systems. NeurIPS: Neural Information
Processing Systems vol. 34, 116–128.'
mla: 'Träuble, Frederik, et al. “Backward-Compatible Prediction Updates: A Probabilistic
Approach.” 35th Conference on Neural Information Processing Systems, vol.
34, 2021, pp. 116–28.'
short: F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf,
P. Gehler, in:, 35th Conference on Neural Information Processing Systems, 2021,
pp. 116–128.
conference:
end_date: 2021-12-10
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2021-12-07
date_created: 2023-08-22T14:05:41Z
date_published: 2021-07-02T00:00:00Z
date_updated: 2023-09-11T11:31:59Z
day: '02'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2107.01057'
intvolume: ' 34'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2107.01057
month: '07'
oa: 1
oa_version: Preprint
page: 116-128
publication: 35th Conference on Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713845393'
publication_status: published
quality_controlled: '1'
status: public
title: 'Backward-compatible prediction updates: A probabilistic approach'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2021'
...
---
OA_place: repository
_id: '14185'
abstract:
- lang: eng
text: A method involves receiving a perceptual representation including a plurality
of feature vectors, and initializing a plurality of slot vectors represented by
a neural network memory unit. Each respective slot vector is configured to represent
a corresponding entity in the perceptual representation. The method also involves
determining an attention matrix based on a product of the plurality of feature
vectors transformed by a key function and the plurality of slot vectors transformed
by a query function. Each respective value of a plurality of values along each
respective dimension of the attention matrix is normalized with respect to the
plurality of values. The method additionally involves determining an update matrix
based on the plurality of feature vectors transformed by a value function and
the attention matrix, and updating the plurality of slot vectors based on the
update matrix by way of the neural network memory unit.
applicant:
- Google LLC
application_date: 2020-07-13
application_number: '16 / 927,018 '
article_processing_charge: No
arxiv: 1
author:
- first_name: Dirk
full_name: Weissenborn, Dirk
last_name: Weissenborn
- first_name: Jakob
full_name: Uszkoreit, Jakob
last_name: Uszkoreit
- first_name: Thomas
full_name: Unterthiner, Thomas
last_name: Unterthiner
- first_name: Aravindh
full_name: Mahendran, Aravindh
last_name: Mahendran
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Thomas
full_name: Kipf, Thomas
last_name: Kipf
- first_name: Georg
full_name: Heigold, Georg
last_name: Heigold
- first_name: Alexey
full_name: Dosovitskiy, Alexey
last_name: Dosovitskiy
citation:
ama: Weissenborn D, Uszkoreit J, Unterthiner T, et al. Object-centric learning with
slot attention. 2021.
apa: Weissenborn, D., Uszkoreit, J., Unterthiner, T., Mahendran, A., Locatello,
F., Kipf, T., … Dosovitskiy, A. (2021). Object-centric learning with slot attention.
chicago: Weissenborn, Dirk, Jakob Uszkoreit, Thomas Unterthiner, Aravindh Mahendran,
Francesco Locatello, Thomas Kipf, Georg Heigold, and Alexey Dosovitskiy. “Object-Centric
Learning with Slot Attention,” 2021.
ieee: D. Weissenborn et al., “Object-centric learning with slot attention.”
2021.
ista: Weissenborn D, Uszkoreit J, Unterthiner T, Mahendran A, Locatello F, Kipf
T, Heigold G, Dosovitskiy A. 2021. Object-centric learning with slot attention.
mla: Weissenborn, Dirk, et al. Object-Centric Learning with Slot Attention.
2021.
short: D. Weissenborn, J. Uszkoreit, T. Unterthiner, A. Mahendran, F. Locatello,
T. Kipf, G. Heigold, A. Dosovitskiy, (2021).
date_created: 2023-08-22T14:07:06Z
date_published: 2021-12-09T00:00:00Z
date_updated: 2025-01-31T11:35:46Z
day: '09'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2006.15055'
ipc: G06N 3/063 ; G06N 3/08 ; G06F 17/16
ipn: US20210383199A1
main_file_link:
- open_access: '1'
url: https://patents.google.com/patent/US20210383199A1/en
month: '12'
oa: 1
oa_version: Published Version
publication_date: 2021-12-09
status: public
title: Object-centric learning with slot attention
type: patent
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '14221'
abstract:
- lang: eng
text: 'The world is structured in countless ways. It may be prudent to enforce corresponding
structural properties to a learning algorithm''s solution, such as incorporating
prior beliefs, natural constraints, or causal structures. Doing so may translate
to faster, more accurate, and more flexible models, which may directly relate
to real-world impact. In this dissertation, we consider two different research
areas that concern structuring a learning algorithm''s solution: when the structure
is known and when it has to be discovered.'
article_number: '2111.13693'
article_processing_charge: No
arxiv: 1
author:
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: Locatello F. Enforcing and discovering structure in machine learning. arXiv.
doi:10.48550/arXiv.2111.13693
apa: Locatello, F. (n.d.). Enforcing and discovering structure in machine learning.
arXiv. https://doi.org/10.48550/arXiv.2111.13693
chicago: Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.”
ArXiv, n.d. https://doi.org/10.48550/arXiv.2111.13693.
ieee: F. Locatello, “Enforcing and discovering structure in machine learning,” arXiv.
.
ista: Locatello F. Enforcing and discovering structure in machine learning. arXiv,
2111.13693.
mla: Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.”
ArXiv, 2111.13693, doi:10.48550/arXiv.2111.13693.
short: F. Locatello, ArXiv (n.d.).
date_created: 2023-08-22T14:23:35Z
date_published: 2021-11-26T00:00:00Z
date_updated: 2024-10-14T12:27:49Z
day: '26'
department:
- _id: FrLo
doi: 10.48550/arXiv.2111.13693
extern: '1'
external_id:
arxiv:
- '2111.13693'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2111.13693
month: '11'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Enforcing and discovering structure in machine learning
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '14332'
abstract:
- lang: eng
text: Learning data representations that are useful for various downstream tasks
is a cornerstone of artificial intelligence. While existing methods are typically
evaluated on downstream tasks such as classification or generative image quality,
we propose to assess representations through their usefulness in downstream control
tasks, such as reaching or pushing objects. By training over 10,000 reinforcement
learning policies, we extensively evaluate to what extent different representation
properties affect out-of-distribution (OOD) generalization. Finally, we demonstrate
zero-shot transfer of these policies from simulation to the real world, without
any domain randomization or fine-tuning. This paper aims to establish the first
systematic characterization of the usefulness of learned representations for real-world
OOD downstream tasks.
article_processing_charge: No
author:
- first_name: Frederik
full_name: Träuble, Frederik
last_name: Träuble
- first_name: Andrea
full_name: Dittadi, Andrea
last_name: Dittadi
- first_name: Manuel
full_name: Wuthrich, Manuel
last_name: Wuthrich
- first_name: Felix
full_name: Widmaier, Felix
last_name: Widmaier
- first_name: Peter Vincent
full_name: Gehler, Peter Vincent
last_name: Gehler
- first_name: Ole
full_name: Winther, Ole
last_name: Winther
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Olivier
full_name: Bachem, Olivier
last_name: Bachem
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
citation:
ama: 'Träuble F, Dittadi A, Wuthrich M, et al. Representation learning for out-of-distribution
generalization in reinforcement learning. In: ICML 2021 Workshop on Unsupervised
Reinforcement Learning. ; 2021.'
apa: Träuble, F., Dittadi, A., Wuthrich, M., Widmaier, F., Gehler, P. V., Winther,
O., … Bauer, S. (2021). Representation learning for out-of-distribution generalization
in reinforcement learning. In ICML 2021 Workshop on Unsupervised Reinforcement
Learning. Virtual.
chicago: Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter
Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf,
and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization
in Reinforcement Learning.” In ICML 2021 Workshop on Unsupervised Reinforcement
Learning, 2021.
ieee: F. Träuble et al., “Representation learning for out-of-distribution
generalization in reinforcement learning,” in ICML 2021 Workshop on Unsupervised
Reinforcement Learning, Virtual, 2021.
ista: 'Träuble F, Dittadi A, Wuthrich M, Widmaier F, Gehler PV, Winther O, Locatello
F, Bachem O, Schölkopf B, Bauer S. 2021. Representation learning for out-of-distribution
generalization in reinforcement learning. ICML 2021 Workshop on Unsupervised Reinforcement
Learning. ICML: International Conference on Machine Learning.'
mla: Träuble, Frederik, et al. “Representation Learning for Out-of-Distribution
Generalization in Reinforcement Learning.” ICML 2021 Workshop on Unsupervised
Reinforcement Learning, 2021.
short: F. Träuble, A. Dittadi, M. Wuthrich, F. Widmaier, P.V. Gehler, O. Winther,
F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, ICML 2021 Workshop on Unsupervised
Reinforcement Learning, 2021.
conference:
end_date: 2021-07-23
location: Virtual
name: 'ICML: International Conference on Machine Learning'
start_date: 2021-07-23
date_created: 2023-09-13T12:43:14Z
date_published: 2021-07-23T00:00:00Z
date_updated: 2023-09-13T12:44:00Z
day: '23'
department:
- _id: FrLo
extern: '1'
language:
- iso: eng
month: '07'
oa_version: None
publication: ICML 2021 Workshop on Unsupervised Reinforcement Learning
publication_status: published
quality_controlled: '1'
status: public
title: Representation learning for out-of-distribution generalization in reinforcement
learning
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '12767'
abstract:
- lang: eng
text: "Several problems in planning and reactive synthesis can be reduced to the
analysis of two-player quantitative graph games. Optimization is one form of analysis.
We argue that in many cases it may be better to replace the optimization problem
with the satisficing problem, where instead of searching for optimal solutions,
the goal is to search for solutions that adhere to a given threshold bound.\r\nThis
work defines and investigates the satisficing problem on a two-player graph game
with the discounted-sum cost model. We show that while the satisficing problem
can be solved using numerical methods just like the optimization problem, this
approach does not render compelling benefits over optimization. When the discount
factor is, however, an integer, we present another approach to satisficing, which
is purely based on automata methods. We show that this approach is algorithmically
more performant – both theoretically and empirically – and demonstrates the broader
applicability of satisficing over optimization."
acknowledgement: We thank anonymous reviewers for valuable inputs. This work is supported
in part by NSF grant 2030859 to the CRA for the CIFellows Project, NSF grants IIS-1527668,
CCF-1704883, IIS-1830549, the ERC CoG 863818 (ForM-SMArt), and an award from the
Maryland Procurement Office.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Suguman
full_name: Bansal, Suguman
last_name: Bansal
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Moshe Y.
full_name: Vardi, Moshe Y.
last_name: Vardi
citation:
ama: 'Bansal S, Chatterjee K, Vardi MY. On satisficing in quantitative games. In:
27th International Conference on Tools and Algorithms for the Construction
and Analysis of Systems. Vol 12651. Springer Nature; 2021:20-37. doi:10.1007/978-3-030-72016-2_2'
apa: 'Bansal, S., Chatterjee, K., & Vardi, M. Y. (2021). On satisficing in quantitative
games. In 27th International Conference on Tools and Algorithms for the Construction
and Analysis of Systems (Vol. 12651, pp. 20–37). Luxembourg City, Luxembourg:
Springer Nature. https://doi.org/10.1007/978-3-030-72016-2_2'
chicago: Bansal, Suguman, Krishnendu Chatterjee, and Moshe Y. Vardi. “On Satisficing
in Quantitative Games.” In 27th International Conference on Tools and Algorithms
for the Construction and Analysis of Systems, 12651:20–37. Springer Nature,
2021. https://doi.org/10.1007/978-3-030-72016-2_2.
ieee: S. Bansal, K. Chatterjee, and M. Y. Vardi, “On satisficing in quantitative
games,” in 27th International Conference on Tools and Algorithms for the Construction
and Analysis of Systems, Luxembourg City, Luxembourg, 2021, vol. 12651, pp.
20–37.
ista: 'Bansal S, Chatterjee K, Vardi MY. 2021. On satisficing in quantitative games.
27th International Conference on Tools and Algorithms for the Construction and
Analysis of Systems. TACAS: Tools and Algorithms for the Construction and Analysis
of Systems, LNCS, vol. 12651, 20–37.'
mla: Bansal, Suguman, et al. “On Satisficing in Quantitative Games.” 27th International
Conference on Tools and Algorithms for the Construction and Analysis of Systems,
vol. 12651, Springer Nature, 2021, pp. 20–37, doi:10.1007/978-3-030-72016-2_2.
short: S. Bansal, K. Chatterjee, M.Y. Vardi, in:, 27th International Conference
on Tools and Algorithms for the Construction and Analysis of Systems, Springer
Nature, 2021, pp. 20–37.
conference:
end_date: 2021-04-01
location: Luxembourg City, Luxembourg
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2021-03-27
date_created: 2023-03-26T22:01:09Z
date_published: 2021-03-21T00:00:00Z
date_updated: 2025-07-10T13:18:02Z
day: '21'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-030-72016-2_2
ec_funded: 1
external_id:
arxiv:
- '2101.02594'
file:
- access_level: open_access
checksum: b020b78b23587ce7610b1aafb4e63438
content_type: application/pdf
creator: dernst
date_created: 2023-03-28T11:00:33Z
date_updated: 2023-03-28T11:00:33Z
file_id: '12777'
file_name: 2021_LNCS_Bansal.pdf
file_size: 747418
relation: main_file
success: 1
file_date_updated: 2023-03-28T11:00:33Z
has_accepted_license: '1'
intvolume: ' 12651'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 20-37
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 27th International Conference on Tools and Algorithms for the Construction
and Analysis of Systems
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783030720155'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: On satisficing in quantitative games
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: 12651
year: '2021'
...
---
_id: '13058'
abstract:
- lang: eng
text: The zip file includes source data used in the main text of the manuscript
"Theory of branching morphogenesis by local interactions and global guidance",
as well as a representative Jupyter notebook to reproduce the main figures. A
sample script for the simulations of branching and annihilating random walks is
also included (Sample_script_for_simulations_of_BARWs.ipynb) to generate exemplary
branched networks under external guidance. A detailed description of the simulation
setup is provided in the supplementary information of the manuscipt.
article_processing_charge: No
author:
- first_name: Mehmet C
full_name: Ucar, Mehmet C
id: 50B2A802-6007-11E9-A42B-EB23E6697425
last_name: Ucar
orcid: 0000-0003-0506-4217
citation:
ama: Ucar MC. Source data for the manuscript “Theory of branching morphogenesis
by local interactions and global guidance.” 2021. doi:10.5281/ZENODO.5257160
apa: Ucar, M. C. (2021). Source data for the manuscript “Theory of branching morphogenesis
by local interactions and global guidance.” Zenodo. https://doi.org/10.5281/ZENODO.5257160
chicago: Ucar, Mehmet C. “Source Data for the Manuscript ‘Theory of Branching Morphogenesis
by Local Interactions and Global Guidance.’” Zenodo, 2021. https://doi.org/10.5281/ZENODO.5257160.
ieee: M. C. Ucar, “Source data for the manuscript ‘Theory of branching morphogenesis
by local interactions and global guidance.’” Zenodo, 2021.
ista: Ucar MC. 2021. Source data for the manuscript ‘Theory of branching morphogenesis
by local interactions and global guidance’, Zenodo, 10.5281/ZENODO.5257160.
mla: Ucar, Mehmet C. Source Data for the Manuscript “Theory of Branching Morphogenesis
by Local Interactions and Global Guidance.” Zenodo, 2021, doi:10.5281/ZENODO.5257160.
short: M.C. Ucar, (2021).
corr_author: '1'
date_created: 2023-05-23T13:46:34Z
date_published: 2021-08-25T00:00:00Z
date_updated: 2025-04-15T06:54:54Z
day: '25'
ddc:
- '570'
department:
- _id: EdHa
doi: 10.5281/ZENODO.5257160
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.5257161
month: '08'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
record:
- id: '10402'
relation: used_in_publication
status: public
status: public
title: Source data for the manuscript "Theory of branching morphogenesis by local
interactions and global guidance"
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: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '13061'
abstract:
- lang: eng
text: Infections early in life can have enduring effects on an organism’s development
and immunity. In this study, we show that this equally applies to developing “superorganisms”
– incipient social insect colonies. When we exposed newly mated Lasius niger ant
queens to a low pathogen dose, their colonies grew more slowly than controls before
winter, but reached similar sizes afterwards. Independent of exposure, queen hibernation
survival improved when the ratio of pupae to workers was small. Queens that reared
fewer pupae before worker emergence exhibited lower pathogen levels, indicating
that high brood rearing efforts interfere with the ability of the queen’s immune
system to suppress pathogen proliferation. Early-life queen pathogen-exposure
also improved the immunocompetence of her worker offspring, as demonstrated by
challenging the workers to the same pathogen a year later. Transgenerational transfer
of the queen’s pathogen experience to her workforce can hence durably reduce the
disease susceptibility of the whole superorganism.
article_processing_charge: No
author:
- first_name: Barbara E
full_name: Casillas Perez, Barbara E
id: 351ED2AA-F248-11E8-B48F-1D18A9856A87
last_name: Casillas Perez
- first_name: Christopher
full_name: Pull, Christopher
id: 3C7F4840-F248-11E8-B48F-1D18A9856A87
last_name: Pull
orcid: 0000-0003-1122-3982
- first_name: Filip
full_name: Naiser, Filip
last_name: Naiser
- first_name: Elisabeth
full_name: Naderlinger, Elisabeth
last_name: Naderlinger
- first_name: Jiri
full_name: Matas, Jiri
last_name: Matas
- first_name: Sylvia
full_name: Cremer, Sylvia
id: 2F64EC8C-F248-11E8-B48F-1D18A9856A87
last_name: Cremer
orcid: 0000-0002-2193-3868
citation:
ama: Casillas Perez BE, Pull C, Naiser F, Naderlinger E, Matas J, Cremer S. Early
queen infection shapes developmental dynamics and induces long-term disease protection
in incipient ant colonies. 2021. doi:10.5061/DRYAD.7PVMCVDTJ
apa: Casillas Perez, B. E., Pull, C., Naiser, F., Naderlinger, E., Matas, J., &
Cremer, S. (2021). Early queen infection shapes developmental dynamics and induces
long-term disease protection in incipient ant colonies. Dryad. https://doi.org/10.5061/DRYAD.7PVMCVDTJ
chicago: Casillas Perez, Barbara E, Christopher Pull, Filip Naiser, Elisabeth Naderlinger,
Jiri Matas, and Sylvia Cremer. “Early Queen Infection Shapes Developmental Dynamics
and Induces Long-Term Disease Protection in Incipient Ant Colonies.” Dryad, 2021.
https://doi.org/10.5061/DRYAD.7PVMCVDTJ.
ieee: B. E. Casillas Perez, C. Pull, F. Naiser, E. Naderlinger, J. Matas, and S.
Cremer, “Early queen infection shapes developmental dynamics and induces long-term
disease protection in incipient ant colonies.” Dryad, 2021.
ista: Casillas Perez BE, Pull C, Naiser F, Naderlinger E, Matas J, Cremer S. 2021.
Early queen infection shapes developmental dynamics and induces long-term disease
protection in incipient ant colonies, Dryad, 10.5061/DRYAD.7PVMCVDTJ.
mla: Casillas Perez, Barbara E., et al. Early Queen Infection Shapes Developmental
Dynamics and Induces Long-Term Disease Protection in Incipient Ant Colonies.
Dryad, 2021, doi:10.5061/DRYAD.7PVMCVDTJ.
short: B.E. Casillas Perez, C. Pull, F. Naiser, E. Naderlinger, J. Matas, S. Cremer,
(2021).
corr_author: '1'
date_created: 2023-05-23T16:14:35Z
date_published: 2021-10-29T00:00:00Z
date_updated: 2025-04-14T13:55:31Z
day: '29'
ddc:
- '570'
department:
- _id: SyCr
doi: 10.5061/DRYAD.7PVMCVDTJ
ec_funded: 1
license: https://creativecommons.org/publicdomain/zero/1.0/
main_file_link:
- open_access: '1'
url: https://doi.org/10.5061/dryad.7pvmcvdtj
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 2649B4DE-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '771402'
name: Epidemics in ant societies on a chip
publisher: Dryad
related_material:
record:
- id: '10284'
relation: used_in_publication
status: public
status: public
title: Early queen infection shapes developmental dynamics and induces long-term disease
protection in incipient ant colonies
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...