---
_id: '14949'
abstract:
- lang: eng
text: Many approaches have been proposed to use diffusion models to augment training
datasets for downstream tasks, such as classification. However, diffusion models
are themselves trained on large datasets, often with noisy annotations, and it
remains an open question to which extent these models contribute to downstream
classification performance. In particular, it remains unclear if they generalize
enough to improve over directly using the additional data of their pre-training
process for augmentation. We systematically evaluate a range of existing methods
to generate images from diffusion models and study new extensions to assess their
benefit for data augmentation. Personalizing diffusion models towards the target
data outperforms simpler prompting strategies. However, using the pre-training
data of the diffusion model alone, via a simple nearest-neighbor retrieval procedure,
leads to even stronger downstream performance. Our study explores the potential
of diffusion models in generating new training data, and surprisingly finds that
these sophisticated models are not yet able to beat a simple and strong image
retrieval baseline on simple downstream vision tasks.
acknowledgement: The authors would like to thank Varad Gunjal and Vishaal Udandarao.
MFB thanks the International Max Planck Research School for Intelligent Systems
(IMPRS-IS).
alternative_title:
- TMLR
article_processing_charge: No
article_type: original
author:
- first_name: Max
full_name: Burg, Max
last_name: Burg
- first_name: Florian
full_name: Wenzel, Florian
last_name: Wenzel
- first_name: Dominik
full_name: Zietlow, Dominik
last_name: Zietlow
- first_name: Max
full_name: Horn, Max
last_name: Horn
- first_name: Osama
full_name: Makansi, Osama
last_name: Makansi
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Chris
full_name: Russell, Chris
last_name: Russell
citation:
ama: Burg M, Wenzel F, Zietlow D, et al. Image retrieval outperforms diffusion models
on data augmentation. Journal of Machine Learning Research. 2023.
apa: Burg, M., Wenzel, F., Zietlow, D., Horn, M., Makansi, O., Locatello, F., &
Russell, C. (2023). Image retrieval outperforms diffusion models on data augmentation.
Journal of Machine Learning Research. ML Research Press.
chicago: Burg, Max, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco
Locatello, and Chris Russell. “Image Retrieval Outperforms Diffusion Models on
Data Augmentation.” Journal of Machine Learning Research. ML Research Press,
2023.
ieee: M. Burg et al., “Image retrieval outperforms diffusion models on data
augmentation,” Journal of Machine Learning Research. ML Research Press,
2023.
ista: Burg M, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. 2023.
Image retrieval outperforms diffusion models on data augmentation. Journal of
Machine Learning Research.
mla: Burg, Max, et al. “Image Retrieval Outperforms Diffusion Models on Data Augmentation.”
Journal of Machine Learning Research, ML Research Press, 2023.
short: M. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell,
Journal of Machine Learning Research (2023).
date_created: 2024-02-07T14:57:39Z
date_published: 2023-12-10T00:00:00Z
date_updated: 2024-02-12T08:30:21Z
day: '10'
ddc:
- '000'
department:
- _id: FrLo
file:
- access_level: open_access
checksum: af87ddea7908923426365347b9c87ba7
content_type: application/pdf
creator: ptazenko
date_created: 2024-02-07T14:57:32Z
date_updated: 2024-02-07T14:57:32Z
file_id: '14950'
file_name: Burg_et_al_2023_Image_retrieval_outperforms.pdf
file_size: 27325153
relation: main_file
file_date_updated: 2024-02-07T14:57:32Z
has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=xflYdGZMpv
month: '12'
oa: 1
oa_version: Published Version
publication: Journal of Machine Learning Research
publication_identifier:
eissn:
- 2835-8856
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
status: public
title: Image retrieval outperforms diffusion models on data augmentation
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
year: '2023'
...
---
OA_place: repository
OA_type: green
_id: '14958'
abstract:
- lang: eng
text: Causal representation learning (CRL) aims at identifying high-level causal
variables from low-level data, e.g. images. Current methods usually assume that
all causal variables are captured in the high-dimensional observations. In this
work, we focus on learning causal representations from data under partial observability,
i.e., when some of the causal variables are not observed in the measurements,
and the set of masked variables changes across the different samples. We introduce
some initial theoretical results for identifying causal variables under partial
observability by exploiting a sparsity regularizer, focusing in particular on
the linear and piecewise linear mixing function case. We provide a theorem that
allows us to identify the causal variables up to permutation and element-wise
linear transformations in the linear case and a lemma that allows us to identify
causal variables up to linear transformation in the piecewise case. Finally, we
provide a conjecture that would allow us to identify the causal variables up to
permutation and element-wise linear transformations also in the piecewise linear
case. We test the theorem and conjecture on simulated data, showing the effectiveness
of our method.
acknowledgement: "This work was initiated at the Second Bellairs Workshop on Causality
held at the Bellairs Research Institute, January 6–13, 2022; we thank all workshop
participants for providing a stimulating research environment. The research of DX
and SM was supported by the Air Force Office of Scientific Research under award
number FA8655-22-1-7155. Any opinions, findings, and conclusions or recommendations
expressed in this material are those of the author(s) and do not necessarily reflect
the views of the United States Air Force. We also thank SURF for the support in
using the Dutch National Supercomputer Snellius. DY was supported by an Amazon fellowship
and the International Max Planck Research School for Intelligent Systems (IMPRS-IS).
Work done outside of Amazon. SL was supported by an IVADO excellence PhD scholarship
and by Samsung Electronics Co., Ldt. JvK acknowledges support from the German Federal
Ministry of Education and Research (BMBF)\r\nthrough the Tübingen AI Center (FKZ:
01IS18039B).\r\n"
article_number: '54'
article_processing_charge: No
author:
- first_name: Danru
full_name: Xu, Danru
last_name: Xu
- first_name: Dingling
full_name: Yao, Dingling
id: d3e02e50-48a8-11ee-8f62-c108061797fa
last_name: Yao
- first_name: Sebastien
full_name: Lachapelle, Sebastien
last_name: Lachapelle
- first_name: Perouz
full_name: Taslakian, Perouz
last_name: Taslakian
- first_name: Julius
full_name: von Kügelgen, Julius
last_name: von Kügelgen
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Sara
full_name: Magliacane, Sara
last_name: Magliacane
citation:
ama: 'Xu D, Yao D, Lachapelle S, et al. A sparsity principle for partially observable
causal representation learning. In: Causal Representation Learning Workshop
at NeurIPS 2023. OpenReview; 2023.'
apa: 'Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello,
F., & Magliacane, S. (2023). A sparsity principle for partially observable
causal representation learning. In Causal Representation Learning Workshop
at NeurIPS 2023. New Orleans, LA, United States: OpenReview.'
chicago: Xu, Danru, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius
von Kügelgen, Francesco Locatello, and Sara Magliacane. “A Sparsity Principle
for Partially Observable Causal Representation Learning.” In Causal Representation
Learning Workshop at NeurIPS 2023. OpenReview, 2023.
ieee: D. Xu et al., “A sparsity principle for partially observable causal
representation learning,” in Causal Representation Learning Workshop at NeurIPS
2023, New Orleans, LA, United States, 2023.
ista: 'Xu D, Yao D, Lachapelle S, Taslakian P, von Kügelgen J, Locatello F, Magliacane
S. 2023. A sparsity principle for partially observable causal representation learning.
Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation
Learning Workshop at NeurIPS, 54.'
mla: Xu, Danru, et al. “A Sparsity Principle for Partially Observable Causal Representation
Learning.” Causal Representation Learning Workshop at NeurIPS 2023, 54,
OpenReview, 2023.
short: D. Xu, D. Yao, S. Lachapelle, P. Taslakian, J. von Kügelgen, F. Locatello,
S. Magliacane, in:, Causal Representation Learning Workshop at NeurIPS 2023, OpenReview,
2023.
conference:
end_date: 2023-12-15
location: New Orleans, LA, United States
name: 'CRL: Causal Representation Learning Workshop at NeurIPS'
start_date: 2023-12-15
date_created: 2024-02-07T15:17:51Z
date_published: 2023-12-05T00:00:00Z
date_updated: 2025-02-04T12:37:34Z
day: '05'
ddc:
- '000'
department:
- _id: FrLo
file:
- access_level: open_access
checksum: 484efc27bda75ed6666044989695d9b6
content_type: application/pdf
creator: dernst
date_created: 2024-02-13T08:50:53Z
date_updated: 2024-02-13T08:50:53Z
file_id: '14982'
file_name: 2023_CRL_Xu.pdf
file_size: 552357
relation: main_file
success: 1
file_date_updated: 2024-02-13T08:50:53Z
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=Whr6uobelR
month: '12'
oa: 1
oa_version: Published Version
publication: Causal Representation Learning Workshop at NeurIPS 2023
publication_status: published
publisher: OpenReview
quality_controlled: '1'
status: public
title: A sparsity principle for partially observable causal representation learning
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
year: '2023'
...
---
_id: '14961'
abstract:
- lang: eng
text: "The use of simulated data in the field of causal discovery is ubiquitous
due to the scarcity of annotated real data. Recently, Reisach et al., 2021 highlighted
the emergence of patterns in simulated linear data, which displays increasing
marginal variance in the casual direction. As an ablation in their experiments,
Montagna et al., 2023 found that similar patterns may emerge in\r\nnonlinear models
for the variance of the score vector $\\nabla \\log p_{\\mathbf{X}}$, and introduced
the ScoreSort algorithm. In this work, we formally define and characterize this
score-sortability pattern of nonlinear additive noise models. We find that it
defines a class of identifiable (bivariate) causal models overlapping with nonlinear
additive noise models. We\r\ntheoretically demonstrate the advantages of ScoreSort
in terms of statistical efficiency compared to prior state-of-the-art score matching-based
methods and empirically show the score-sortability of the most common synthetic
benchmarks in the literature. Our findings remark (1) the lack of diversity in
the data as an important limitation in the evaluation of nonlinear causal discovery
approaches, (2) the importance of thoroughly testing different settings within
a problem class, and (3) the importance of analyzing statistical properties in\r\ncausal
discovery, where research is often limited to defining identifiability conditions
of the model. "
article_number: '2310.14246'
article_processing_charge: No
arxiv: 1
author:
- first_name: Francesco
full_name: Montagna, Francesco
last_name: Montagna
- first_name: Nicoletta
full_name: Noceti, Nicoletta
last_name: Noceti
- first_name: Lorenzo
full_name: Rosasco, Lorenzo
last_name: Rosasco
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
citation:
ama: Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery
of nonlinear models by score matching. arXiv. doi:10.48550/arXiv.2310.14246
apa: Montagna, F., Noceti, N., Rosasco, L., & Locatello, F. (n.d.). Shortcuts
for causal discovery of nonlinear models by score matching. arXiv. https://doi.org/10.48550/arXiv.2310.14246
chicago: Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, and Francesco Locatello.
“Shortcuts for Causal Discovery of Nonlinear Models by Score Matching.” ArXiv,
n.d. https://doi.org/10.48550/arXiv.2310.14246.
ieee: F. Montagna, N. Noceti, L. Rosasco, and F. Locatello, “Shortcuts for causal
discovery of nonlinear models by score matching,” arXiv. .
ista: Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery
of nonlinear models by score matching. arXiv, 2310.14246.
mla: Montagna, Francesco, et al. “Shortcuts for Causal Discovery of Nonlinear Models
by Score Matching.” ArXiv, 2310.14246, doi:10.48550/arXiv.2310.14246.
short: F. Montagna, N. Noceti, L. Rosasco, F. Locatello, ArXiv (n.d.).
corr_author: '1'
date_created: 2024-02-08T15:31:46Z
date_published: 2023-10-22T00:00:00Z
date_updated: 2024-10-09T21:08:10Z
day: '22'
department:
- _id: FrLo
doi: 10.48550/arXiv.2310.14246
external_id:
arxiv:
- '2310.14246'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2310.14246
month: '10'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Shortcuts for causal discovery of nonlinear models by score matching
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14962'
abstract:
- lang: eng
text: "In this paper, we show that recent advances in video representation learning\r\nand
pre-trained vision-language models allow for substantial improvements in\r\nself-supervised
video object localization. We propose a method that first\r\nlocalizes objects
in videos via a slot attention approach and then assigns text\r\nto the obtained
slots. The latter is achieved by an unsupervised way to read\r\nlocalized semantic
information from the pre-trained CLIP model. The resulting\r\nvideo object localization
is entirely unsupervised apart from the implicit\r\nannotation contained in CLIP,
and it is effectively the first unsupervised\r\napproach that yields good results
on regular video benchmarks."
article_number: '2309.09858'
article_processing_charge: No
arxiv: 1
author:
- first_name: Ke
full_name: Fan, Ke
last_name: Fan
- first_name: Zechen
full_name: Bai, Zechen
last_name: Bai
- first_name: Tianjun
full_name: Xiao, Tianjun
last_name: Xiao
- first_name: Dominik
full_name: Zietlow, Dominik
last_name: Zietlow
- first_name: Max
full_name: Horn, Max
last_name: Horn
- first_name: Zixu
full_name: Zhao, Zixu
last_name: Zhao
- first_name: Carl-Johann Simon-Gabriel
full_name: Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel
last_name: Carl-Johann Simon-Gabriel
- first_name: Mike Zheng
full_name: Shou, Mike Zheng
last_name: Shou
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Bernt
full_name: Schiele, Bernt
last_name: Schiele
- first_name: Thomas
full_name: Brox, Thomas
last_name: Brox
- first_name: Zheng
full_name: Zhang, Zheng
last_name: Zhang
- first_name: Yanwei
full_name: Fu, Yanwei
last_name: Fu
- first_name: Tong
full_name: He, Tong
last_name: He
citation:
ama: Fan K, Bai Z, Xiao T, et al. Unsupervised open-vocabulary object localization
in videos. arXiv. doi:10.48550/arXiv.2309.09858
apa: Fan, K., Bai, Z., Xiao, T., Zietlow, D., Horn, M., Zhao, Z., … He, T. (n.d.).
Unsupervised open-vocabulary object localization in videos. arXiv. https://doi.org/10.48550/arXiv.2309.09858
chicago: Fan, Ke, Zechen Bai, Tianjun Xiao, Dominik Zietlow, Max Horn, Zixu Zhao,
Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, et al. “Unsupervised Open-Vocabulary
Object Localization in Videos.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2309.09858.
ieee: K. Fan et al., “Unsupervised open-vocabulary object localization in
videos,” arXiv. .
ista: Fan K, Bai Z, Xiao T, Zietlow D, Horn M, Zhao Z, Carl-Johann Simon-Gabriel
C-JS-G, Shou MZ, Locatello F, Schiele B, Brox T, Zhang Z, Fu Y, He T. Unsupervised
open-vocabulary object localization in videos. arXiv, 2309.09858.
mla: Fan, Ke, et al. “Unsupervised Open-Vocabulary Object Localization in Videos.”
ArXiv, 2309.09858, doi:10.48550/arXiv.2309.09858.
short: K. Fan, Z. Bai, T. Xiao, D. Zietlow, M. Horn, Z. Zhao, C.-J.S.-G. Carl-Johann
Simon-Gabriel, M.Z. Shou, F. Locatello, B. Schiele, T. Brox, Z. Zhang, Y. Fu,
T. He, ArXiv (n.d.).
date_created: 2024-02-08T15:33:39Z
date_published: 2023-09-18T00:00:00Z
date_updated: 2024-02-12T10:12:22Z
day: '18'
department:
- _id: FrLo
doi: 10.48550/arXiv.2309.09858
extern: '1'
external_id:
arxiv:
- '2309.09858'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2309.09858
month: '09'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Unsupervised open-vocabulary object localization in videos
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14963'
abstract:
- lang: eng
text: "Unsupervised object-centric learning methods allow the partitioning of scenes\r\ninto
entities without additional localization information and are excellent\r\ncandidates
for reducing the annotation burden of multiple-object tracking (MOT)\r\npipelines.
Unfortunately, they lack two key properties: objects are often split\r\ninto parts
and are not consistently tracked over time. In fact,\r\nstate-of-the-art models
achieve pixel-level accuracy and temporal consistency\r\nby relying on supervised
object detection with additional ID labels for the\r\nassociation through time.
This paper proposes a video object-centric model for\r\nMOT. It consists of an
index-merge module that adapts the object-centric slots\r\ninto detection outputs
and an object memory module that builds complete object\r\nprototypes to handle
occlusions. Benefited from object-centric learning, we\r\nonly require sparse
detection labels (0%-6.25%) for object localization and\r\nfeature binding. Relying
on our self-supervised\r\nExpectation-Maximization-inspired loss for object association,
our approach\r\nrequires no ID labels. Our experiments significantly narrow the
gap between the\r\nexisting object-centric model and the fully supervised state-of-the-art
and\r\noutperform several unsupervised trackers."
article_number: '2309.00233'
article_processing_charge: No
arxiv: 1
author:
- first_name: Zixu
full_name: Zhao, Zixu
last_name: Zhao
- first_name: Jiaze
full_name: Wang, Jiaze
last_name: Wang
- first_name: Max
full_name: Horn, Max
last_name: Horn
- first_name: Yizhuo
full_name: Ding, Yizhuo
last_name: Ding
- first_name: Tong
full_name: He, Tong
last_name: He
- first_name: Zechen
full_name: Bai, Zechen
last_name: Bai
- first_name: Dominik
full_name: Zietlow, Dominik
last_name: Zietlow
- first_name: Carl-Johann Simon-Gabriel
full_name: Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel
last_name: Carl-Johann Simon-Gabriel
- first_name: Bing
full_name: Shuai, Bing
last_name: Shuai
- first_name: Zhuowen
full_name: Tu, Zhuowen
last_name: Tu
- first_name: Thomas
full_name: Brox, Thomas
last_name: Brox
- first_name: Bernt
full_name: Schiele, Bernt
last_name: Schiele
- first_name: Yanwei
full_name: Fu, Yanwei
last_name: Fu
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Zheng
full_name: Zhang, Zheng
last_name: Zhang
- first_name: Tianjun
full_name: Xiao, Tianjun
last_name: Xiao
citation:
ama: Zhao Z, Wang J, Horn M, et al. Object-centric multiple object tracking. arXiv.
doi:10.48550/arXiv.2309.00233
apa: Zhao, Z., Wang, J., Horn, M., Ding, Y., He, T., Bai, Z., … Xiao, T. (n.d.).
Object-centric multiple object tracking. arXiv. https://doi.org/10.48550/arXiv.2309.00233
chicago: Zhao, Zixu, Jiaze Wang, Max Horn, Yizhuo Ding, Tong He, Zechen Bai, Dominik
Zietlow, et al. “Object-Centric Multiple Object Tracking.” ArXiv, n.d.
https://doi.org/10.48550/arXiv.2309.00233.
ieee: Z. Zhao et al., “Object-centric multiple object tracking,” arXiv.
.
ista: Zhao Z, Wang J, Horn M, Ding Y, He T, Bai Z, Zietlow D, Carl-Johann Simon-Gabriel
C-JS-G, Shuai B, Tu Z, Brox T, Schiele B, Fu Y, Locatello F, Zhang Z, Xiao T.
Object-centric multiple object tracking. arXiv, 2309.00233.
mla: Zhao, Zixu, et al. “Object-Centric Multiple Object Tracking.” ArXiv,
2309.00233, doi:10.48550/arXiv.2309.00233.
short: Z. Zhao, J. Wang, M. Horn, Y. Ding, T. He, Z. Bai, D. Zietlow, C.-J.S.-G.
Carl-Johann Simon-Gabriel, B. Shuai, Z. Tu, T. Brox, B. Schiele, Y. Fu, F. Locatello,
Z. Zhang, T. Xiao, ArXiv (n.d.).
date_created: 2024-02-08T15:34:43Z
date_published: 2023-09-01T00:00:00Z
date_updated: 2024-02-12T10:16:21Z
day: '01'
department:
- _id: FrLo
doi: 10.48550/arXiv.2309.00233
extern: '1'
external_id:
arxiv:
- '2309.00233'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.2309.00233'
month: '09'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Object-centric multiple object tracking
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
OA_place: repository
_id: '14965'
abstract:
- lang: eng
text: 'A method of determining a correspondence between a first biological property
of a cell and one or more further biological properties of cells is provided.
The first biological property and the further biological properties are determined
by different analysis techniques and each are contained in a respective one of
a plurality of sets of biological properties. The method includes the steps of:
converting the plurality of sets of biological properties into corresponding representations
in a representation format which is invariant to the technologies used to derive
the biological properties; determining, in said representation format, a representation
from each of the converted sets of further biological properties which most closely
matches the first representation of the first biological property; and re-converting
the determined representations from the representation format back to the biological
properties associated with the determined representations and thereby determining
a correspondence between the first biological property and each of the further
biological properties.'
applicant:
- ETH Zürich
application_date: 2021-04-21
application_number: PCT/EP2021/060318
article_processing_charge: No
author:
- first_name: Joanna
full_name: Ficek, Joanna
last_name: Ficek
- first_name: Kjong-Van
full_name: Lehmann, Kjong-Van
last_name: Lehmann
- 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: 'Raetsch, Gunnar '
last_name: Raetsch
- first_name: Stefan
full_name: Stark, Stefan
last_name: Stark
citation:
ama: Ficek J, Lehmann K-V, Locatello F, Raetsch G, Stark S. Methods of determining
correspondences between biological properties of cells. 2023.
apa: Ficek, J., Lehmann, K.-V., Locatello, F., Raetsch, G., & Stark, S. (2023).
Methods of determining correspondences between biological properties of cells.
chicago: Ficek, Joanna, Kjong-Van Lehmann, Francesco Locatello, Gunnar Raetsch,
and Stefan Stark. “Methods of Determining Correspondences between Biological Properties
of Cells,” 2023.
ieee: J. Ficek, K.-V. Lehmann, F. Locatello, G. Raetsch, and S. Stark, “Methods
of determining correspondences between biological properties of cells.” 2023.
ista: Ficek J, Lehmann K-V, Locatello F, Raetsch G, Stark S. 2023. Methods of determining
correspondences between biological properties of cells.
mla: Ficek, Joanna, et al. Methods of Determining Correspondences between Biological
Properties of Cells. 2023.
short: J. Ficek, K.-V. Lehmann, F. Locatello, G. Raetsch, S. Stark, (2023).
date_created: 2024-02-08T15:52:21Z
date_published: 2023-05-25T00:00:00Z
date_updated: 2025-01-29T10:53:48Z
day: '25'
ddc:
- '540'
department:
- _id: FrLo
extern: '1'
file:
- access_level: open_access
checksum: 55ed444b176b48e4fb4d609ea895de36
content_type: application/pdf
creator: ptazenko
date_created: 2024-02-08T15:41:51Z
date_updated: 2024-02-08T15:41:51Z
file_id: '14966'
file_name: Patent_FrLo_US20230162818A1.pdf
file_size: 2893462
relation: main_file
success: 1
file_date_updated: 2024-02-08T15:41:51Z
has_accepted_license: '1'
ipc: C12Q1/68 ; G06V10/82 ; G06V20/69 ; G16B40/30
ipn: US20230162818A1
month: '05'
oa: 1
oa_version: Published Version
page: '9'
publication_date: 2023-05-25
status: public
title: Methods of determining correspondences between biological properties of cells
type: patent
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14974'
abstract:
- lang: eng
text: "The field of machine learning and AI has witnessed remarkable breakthroughs
with the emergence of LLMs, which have also sparked a lively debate in the causal
community. As researchers in this field, we are interested in exploring how LLMs
relate to causality research, and how we can leverage the technology to advance
it. In the second conference of Causal Learning and Reasoning (CLeaR), 2023, we
held a round table discussion to gather and integrate the diverse perspectives
of the CLeaR community on this topic.\r\nThere is a general consensus that LLMs
are not yet capable of causal reasoning at the current\r\nstage but has a lot
of potential with public available information by CLeaR 2023. Enhancing causal
machine learning is vital not only for its own sake but also to help LLMs improve
their performance, especially regarding trustworthiness. In this document, we
present both the summary and the raw outcome of the round table discussion. We
acknowledge that with the progress of both fields, the opportunities and impact
may rapidly change. We will repeat the same exercise in CLeaR 2024 to document
the evolution."
article_processing_charge: No
author:
- first_name: Cheng
full_name: Zhang, Cheng
last_name: Zhang
- first_name: Dominik
full_name: Janzing, Dominik
last_name: Janzing
- first_name: 'Mihaela '
full_name: 'van der Schaar, Mihaela '
last_name: van der Schaar
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Peter
full_name: Spirtes, Peter
last_name: Spirtes
- first_name: Kun
full_name: Zhang, Kun
last_name: Zhang
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Caroline
full_name: Uhler, Caroline
id: 49ADD78E-F248-11E8-B48F-1D18A9856A87
last_name: Uhler
orcid: 0000-0002-7008-0216
citation:
ama: 'Zhang C, Janzing D, van der Schaar M, et al. Causality in the time of LLMs:
Round table discussion results of CLeaR 2023. In: 2nd Conference on Causal
Learning and Reasoning.'
apa: 'Zhang, C., Janzing, D., van der Schaar, M., Locatello, F., Spirtes, P., Zhang,
K., … Uhler, C. (n.d.). Causality in the time of LLMs: Round table discussion
results of CLeaR 2023. In 2nd Conference on Causal Learning and Reasoning.
Tübingen, Germany.'
chicago: 'Zhang, Cheng, Dominik Janzing, Mihaela van der Schaar, Francesco Locatello,
Peter Spirtes, Kun Zhang, Bernhard Schölkopf, and Caroline Uhler. “Causality in
the Time of LLMs: Round Table Discussion Results of CLeaR 2023.” In 2nd Conference
on Causal Learning and Reasoning, n.d.'
ieee: 'C. Zhang et al., “Causality in the time of LLMs: Round table discussion
results of CLeaR 2023,” in 2nd Conference on Causal Learning and Reasoning,
Tübingen, Germany.'
ista: 'Zhang C, Janzing D, van der Schaar M, Locatello F, Spirtes P, Zhang K, Schölkopf
B, Uhler C. Causality in the time of LLMs: Round table discussion results of CLeaR
2023. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal
Learning and Reasoning.'
mla: 'Zhang, Cheng, et al. “Causality in the Time of LLMs: Round Table Discussion
Results of CLeaR 2023.” 2nd Conference on Causal Learning and Reasoning.'
short: C. Zhang, D. Janzing, M. van der Schaar, F. Locatello, P. Spirtes, K. Zhang,
B. Schölkopf, C. Uhler, in:, 2nd Conference on Causal Learning and Reasoning,
n.d.
conference:
end_date: 2023-04-14
location: Tübingen, Germany
name: 'CLeaR: Conference on Causal Learning and Reasoning'
start_date: 2023-04-11
date_created: 2024-02-08T16:03:18Z
date_published: 2023-05-01T00:00:00Z
date_updated: 2025-08-05T11:19:37Z
day: '01'
ddc:
- '000'
department:
- _id: FrLo
extern: '1'
file:
- access_level: open_access
checksum: 105ff58e55de866ce76967f3a95e82f7
content_type: application/pdf
creator: ptazenko
date_created: 2024-02-08T16:03:08Z
date_updated: 2024-02-08T16:03:08Z
file_id: '14975'
file_name: CLeaR23_roundtable_discussion.pdf
file_size: 215629
relation: main_file
file_date_updated: 2024-02-08T16:03:08Z
has_accepted_license: '1'
language:
- iso: eng
month: '05'
oa: 1
oa_version: Submitted Version
publication: 2nd Conference on Causal Learning and Reasoning
publication_status: submitted
quality_controlled: '1'
status: public
title: 'Causality in the time of LLMs: Round table discussion results of CLeaR 2023'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14985'
abstract:
- lang: eng
text: Lead sulfide (PbS) presents large potential in thermoelectric application
due to its earth-abundant S element. However, its inferior average ZT (ZTave)
value makes PbS less competitive with its analogs PbTe and PbSe. To promote its
thermoelectric performance, this study implements strategies of continuous Se
alloying and Cu interstitial doping to synergistically tune thermal and electrical
transport properties in n-type PbS. First, the lattice parameter of 5.93 Å in
PbS is linearly expanded to 6.03 Å in PbS0.5Se0.5 with increasing Se alloying
content. This expanded lattice in Se-alloyed PbS not only intensifies phonon scattering
but also facilitates the formation of Cu interstitials. Based on the PbS0.6Se0.4
content with the minimal lattice thermal conductivity, Cu interstitials are introduced
to improve the electron density, thus boosting the peak power factor, from 3.88 μW cm−1 K−2
in PbS0.6Se0.4 to 20.58 μW cm−1 K−2 in PbS0.6Se0.4−1%Cu. Meanwhile, the lattice
thermal conductivity in PbS0.6Se0.4−x%Cu (x = 0–2) is further suppressed due to
the strong strain field caused by Cu interstitials. Finally, with the lowered
thermal conductivity and high electrical transport properties, a peak ZT ~1.1
and ZTave ~0.82 can be achieved in PbS0.6Se0.4 − 1%Cu at 300–773K, which outperforms
previously reported n-type PbS.
acknowledgement: 'The authors would like to acknowledge the strong supportof microstructure
observation from Center for HighPressure Science and Technology Advanced Research(HPSTAR).
We acknowledge the financial support fromthe National Natural Science Foundation of China:52172236,
the Fundamental Research Funds for theCentral Universities: xtr042021007, Top Young
TalentsProgramme of Xi''an Jiaotong University and NationalScience Fund for Distinguished
Young Scholars: 51925101.'
article_processing_charge: Yes
article_type: original
author:
- first_name: Zhengtao
full_name: Liu, Zhengtao
last_name: Liu
- first_name: Tao
full_name: Hong, Tao
last_name: Hong
- first_name: Liqing
full_name: Xu, Liqing
last_name: Xu
- first_name: Sining
full_name: Wang, Sining
last_name: Wang
- first_name: Xiang
full_name: Gao, Xiang
last_name: Gao
- first_name: Cheng
full_name: Chang, Cheng
id: 9E331C2E-9F27-11E9-AE48-5033E6697425
last_name: Chang
orcid: 0000-0002-9515-4277
- first_name: Xiangdong
full_name: Ding, Xiangdong
last_name: Ding
- first_name: Yu
full_name: Xiao, Yu
last_name: Xiao
- first_name: Li‐Dong
full_name: Zhao, Li‐Dong
last_name: Zhao
citation:
ama: Liu Z, Hong T, Xu L, et al. Lattice expansion enables interstitial doping to
achieve a high average ZT in n‐type PbS. Interdisciplinary Materials. 2023;2(1):161-170.
doi:10.1002/idm2.12056
apa: Liu, Z., Hong, T., Xu, L., Wang, S., Gao, X., Chang, C., … Zhao, L. (2023).
Lattice expansion enables interstitial doping to achieve a high average ZT in
n‐type PbS. Interdisciplinary Materials. Wiley. https://doi.org/10.1002/idm2.12056
chicago: Liu, Zhengtao, Tao Hong, Liqing Xu, Sining Wang, Xiang Gao, Cheng Chang,
Xiangdong Ding, Yu Xiao, and Li‐Dong Zhao. “Lattice Expansion Enables Interstitial
Doping to Achieve a High Average ZT in N‐type PbS.” Interdisciplinary Materials.
Wiley, 2023. https://doi.org/10.1002/idm2.12056.
ieee: Z. Liu et al., “Lattice expansion enables interstitial doping to achieve
a high average ZT in n‐type PbS,” Interdisciplinary Materials, vol. 2,
no. 1. Wiley, pp. 161–170, 2023.
ista: Liu Z, Hong T, Xu L, Wang S, Gao X, Chang C, Ding X, Xiao Y, Zhao L. 2023.
Lattice expansion enables interstitial doping to achieve a high average ZT in
n‐type PbS. Interdisciplinary Materials. 2(1), 161–170.
mla: Liu, Zhengtao, et al. “Lattice Expansion Enables Interstitial Doping to Achieve
a High Average ZT in N‐type PbS.” Interdisciplinary Materials, vol. 2,
no. 1, Wiley, 2023, pp. 161–70, doi:10.1002/idm2.12056.
short: Z. Liu, T. Hong, L. Xu, S. Wang, X. Gao, C. Chang, X. Ding, Y. Xiao, L. Zhao,
Interdisciplinary Materials 2 (2023) 161–170.
date_created: 2024-02-14T12:12:17Z
date_published: 2023-01-01T00:00:00Z
date_updated: 2024-02-19T10:01:26Z
day: '01'
ddc:
- '540'
department:
- _id: MaIb
doi: 10.1002/idm2.12056
file:
- access_level: open_access
checksum: 7b5e8210ef1434feb173022c6dbbee0c
content_type: application/pdf
creator: dernst
date_created: 2024-02-19T09:58:32Z
date_updated: 2024-02-19T09:58:32Z
file_id: '15015'
file_name: 2023_InterdiscMaterials_Liu.pdf
file_size: 4675941
relation: main_file
success: 1
file_date_updated: 2024-02-19T09:58:32Z
has_accepted_license: '1'
intvolume: ' 2'
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 161-170
publication: Interdisciplinary Materials
publication_identifier:
eissn:
- 2767-441X
publication_status: published
publisher: Wiley
quality_controlled: '1'
status: public
title: Lattice expansion enables interstitial doping to achieve a high average ZT
in n‐type PbS
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: 2
year: '2023'
...
---
_id: '14989'
abstract:
- lang: eng
text: "Encryption alone is not enough for secure end-to end encrypted messaging:
a server must also honestly serve public keys to users. Key transparency has been
presented as an efficient\r\nsolution for detecting (and hence deterring) a server
that attempts to dishonestly serve keys. Key transparency involves two major components:
(1) a username to public key mapping, stored and cryptographically committed to
by the server, and, (2) an outof-band consistency protocol for serving short commitments
to users. In the setting of real-world deployments and supporting production scale,
new challenges must be considered for both of these components. We enumerate these
challenges and provide solutions to address them. In particular, we design and
implement a memory-optimized and privacy-preserving verifiable data structure
for committing to the username to public key store.\r\nTo make this implementation
viable for production, we also integrate support for persistent and distributed
storage. We also propose a future-facing solution, termed “compaction”, as\r\na
mechanism for mitigating practical issues that arise from dealing with infinitely
growing server data structures. Finally, we implement a consensusless solution
that achieves the minimum requirements for a service that consistently distributes
commitments for a transparency application, providing a much more efficient protocol
for distributing small and consistent\r\ncommitments to users. This culminates
in our production-grade implementation of a key transparency system (Parakeet)
which we have open-sourced, along with a demonstration of feasibility through
our benchmarks."
acknowledgement: This work is supported by the Novi team at Meta and funded in part
by IC3 industry partners and NSF grant 1943499.
article_processing_charge: No
author:
- first_name: Harjasleen
full_name: Malvai, Harjasleen
last_name: Malvai
- first_name: Eleftherios
full_name: Kokoris Kogias, Eleftherios
id: f5983044-d7ef-11ea-ac6d-fd1430a26d30
last_name: Kokoris Kogias
orcid: 0000-0002-8827-3382
- first_name: Alberto
full_name: Sonnino, Alberto
last_name: Sonnino
- first_name: Esha
full_name: Ghosh, Esha
last_name: Ghosh
- first_name: Ercan
full_name: Oztürk, Ercan
last_name: Oztürk
- first_name: Kevin
full_name: Lewi, Kevin
last_name: Lewi
- first_name: Sean
full_name: Lawlor, Sean
last_name: Lawlor
citation:
ama: 'Malvai H, Kokoris Kogias E, Sonnino A, et al. Parakeet: Practical key transparency
for end-to-end eEncrypted messaging. In: Proceedings of the 2023 Network and
Distributed System Security Symposium. Internet Society; 2023. doi:10.14722/ndss.2023.24545'
apa: 'Malvai, H., Kokoris Kogias, E., Sonnino, A., Ghosh, E., Oztürk, E., Lewi,
K., & Lawlor, S. (2023). Parakeet: Practical key transparency for end-to-end
eEncrypted messaging. In Proceedings of the 2023 Network and Distributed System
Security Symposium. San Diego, CA, United States: Internet Society. https://doi.org/10.14722/ndss.2023.24545'
chicago: 'Malvai, Harjasleen, Eleftherios Kokoris Kogias, Alberto Sonnino, Esha
Ghosh, Ercan Oztürk, Kevin Lewi, and Sean Lawlor. “Parakeet: Practical Key Transparency
for End-to-End EEncrypted Messaging.” In Proceedings of the 2023 Network and
Distributed System Security Symposium. Internet Society, 2023. https://doi.org/10.14722/ndss.2023.24545.'
ieee: 'H. Malvai et al., “Parakeet: Practical key transparency for end-to-end
eEncrypted messaging,” in Proceedings of the 2023 Network and Distributed System
Security Symposium, San Diego, CA, United States, 2023.'
ista: 'Malvai H, Kokoris Kogias E, Sonnino A, Ghosh E, Oztürk E, Lewi K, Lawlor
S. 2023. Parakeet: Practical key transparency for end-to-end eEncrypted messaging.
Proceedings of the 2023 Network and Distributed System Security Symposium. NDSS:
Network and Distributed Systems Security.'
mla: 'Malvai, Harjasleen, et al. “Parakeet: Practical Key Transparency for End-to-End
EEncrypted Messaging.” Proceedings of the 2023 Network and Distributed System
Security Symposium, Internet Society, 2023, doi:10.14722/ndss.2023.24545.'
short: H. Malvai, E. Kokoris Kogias, A. Sonnino, E. Ghosh, E. Oztürk, K. Lewi, S.
Lawlor, in:, Proceedings of the 2023 Network and Distributed System Security Symposium,
Internet Society, 2023.
conference:
end_date: 2023-03-03
location: San Diego, CA, United States
name: 'NDSS: Network and Distributed Systems Security'
start_date: 2023-02-27
date_created: 2024-02-14T14:20:40Z
date_published: 2023-03-01T00:00:00Z
date_updated: 2026-06-18T17:41:59Z
day: '01'
ddc:
- '000'
department:
- _id: ElKo
doi: 10.14722/ndss.2023.24545
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2023/081
month: '03'
oa: 1
oa_version: Published Version
publication: Proceedings of the 2023 Network and Distributed System Security Symposium
publication_identifier:
isbn:
- '1891562835'
publication_status: published
publisher: Internet Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Parakeet: Practical key transparency for end-to-end eEncrypted messaging'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14990'
abstract:
- lang: eng
text: The software artefact to evaluate the approximation of stationary distributions
implementation.
article_processing_charge: No
author:
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
citation:
ama: 'Meggendorfer T. Artefact for: Correct Approximation of Stationary Distributions.
2023. doi:10.5281/ZENODO.7548214'
apa: 'Meggendorfer, T. (2023). Artefact for: Correct Approximation of Stationary
Distributions. Zenodo. https://doi.org/10.5281/ZENODO.7548214'
chicago: 'Meggendorfer, Tobias. “Artefact for: Correct Approximation of Stationary
Distributions.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.7548214.'
ieee: 'T. Meggendorfer, “Artefact for: Correct Approximation of Stationary Distributions.”
Zenodo, 2023.'
ista: 'Meggendorfer T. 2023. Artefact for: Correct Approximation of Stationary Distributions,
Zenodo, 10.5281/ZENODO.7548214.'
mla: 'Meggendorfer, Tobias. Artefact for: Correct Approximation of Stationary
Distributions. Zenodo, 2023, doi:10.5281/ZENODO.7548214.'
short: T. Meggendorfer, (2023).
corr_author: '1'
date_created: 2024-02-14T14:27:06Z
date_published: 2023-01-18T00:00:00Z
date_updated: 2025-09-09T12:28:12Z
day: '18'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.5281/ZENODO.7548214
has_accepted_license: '1'
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.7548214
month: '01'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
record:
- id: '13139'
relation: used_in_publication
status: public
status: public
title: 'Artefact for: Correct Approximation of Stationary Distributions'
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: '2023'
...
---
_id: '14991'
abstract:
- lang: eng
text: This repository contains the data, scripts, WRF codes and files required to
reproduce the results of the manuscript "Assessing Memory in Convection Schemes
Using Idealized Tests" submitted to the Journal of Advances in Modeling Earth
Systems (JAMES).
article_processing_charge: No
author:
- first_name: Yi-Ling
full_name: Hwong, Yi-Ling
id: 1217aa61-4dd1-11ec-9ac3-f2ba3f17ee22
last_name: Hwong
orcid: 0000-0001-9281-3479
- first_name: Maxime
full_name: Colin, Maxime
last_name: Colin
- first_name: Philipp
full_name: Aglas, Philipp
id: 02eace56-97fc-11ee-b81a-f0939ca85a77
last_name: Aglas
- 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: Steven C.
full_name: Sherwood, Steven C.
last_name: Sherwood
citation:
ama: Hwong Y-L, Colin M, Aglas P, Muller CJ, Sherwood SC. Data-assessing memory
in convection schemes using idealized tests. 2023. doi:10.5281/ZENODO.7757041
apa: Hwong, Y.-L., Colin, M., Aglas, P., Muller, C. J., & Sherwood, S. C. (2023).
Data-assessing memory in convection schemes using idealized tests. Zenodo. https://doi.org/10.5281/ZENODO.7757041
chicago: Hwong, Yi-Ling, Maxime Colin, Philipp Aglas, Caroline J Muller, and Steven
C. Sherwood. “Data-Assessing Memory in Convection Schemes Using Idealized Tests.”
Zenodo, 2023. https://doi.org/10.5281/ZENODO.7757041.
ieee: Y.-L. Hwong, M. Colin, P. Aglas, C. J. Muller, and S. C. Sherwood, “Data-assessing
memory in convection schemes using idealized tests.” Zenodo, 2023.
ista: Hwong Y-L, Colin M, Aglas P, Muller CJ, Sherwood SC. 2023. Data-assessing
memory in convection schemes using idealized tests, Zenodo, 10.5281/ZENODO.7757041.
mla: Hwong, Yi-Ling, et al. Data-Assessing Memory in Convection Schemes Using
Idealized Tests. Zenodo, 2023, doi:10.5281/ZENODO.7757041.
short: Y.-L. Hwong, M. Colin, P. Aglas, C.J. Muller, S.C. Sherwood, (2023).
corr_author: '1'
date_created: 2024-02-14T14:37:57Z
date_published: 2023-06-23T00:00:00Z
date_updated: 2025-09-09T13:35:40Z
day: '23'
ddc:
- '550'
department:
- _id: CaMu
doi: 10.5281/ZENODO.7757041
ec_funded: 1
has_accepted_license: '1'
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.7757041
month: '06'
oa: 1
oa_version: Published Version
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publisher: Zenodo
related_material:
record:
- id: '14654'
relation: used_in_publication
status: public
status: public
title: Data-assessing memory in convection schemes using idealized tests
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: '2023'
...
---
_id: '14992'
abstract:
- lang: eng
text: In this chapter we first review the Levy–Lieb functional, which gives the
lowest kinetic and interaction energy that can be reached with all possible quantum
states having a given density. We discuss two possible convex generalizations
of this functional, corresponding to using mixed canonical and grand-canonical
states, respectively. We present some recent works about the local density approximation,
in which the functionals get replaced by purely local functionals constructed
using the uniform electron gas energy per unit volume. We then review the known
upper and lower bounds on the Levy–Lieb functionals. We start with the kinetic
energy alone, then turn to the classical interaction alone, before we are able
to put everything together. A later section is devoted to the Hohenberg–Kohn theorem
and the role of many-body unique continuation in its proof.
alternative_title:
- Mathematics and Molecular Modeling
article_processing_charge: No
arxiv: 1
author:
- first_name: Mathieu
full_name: Lewin, Mathieu
last_name: Lewin
- first_name: Elliott H.
full_name: Lieb, Elliott H.
last_name: Lieb
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: 'Lewin M, Lieb EH, Seiringer R. Universal Functionals in Density Functional
Theory. In: Cances E, Friesecke G, eds. Density Functional Theory. 1st
ed. MAMOMO. Springer; 2023:115-182. doi:10.1007/978-3-031-22340-2_3'
apa: Lewin, M., Lieb, E. H., & Seiringer, R. (2023). Universal Functionals in
Density Functional Theory. In E. Cances & G. Friesecke (Eds.), Density
Functional Theory (1st ed., pp. 115–182). Springer. https://doi.org/10.1007/978-3-031-22340-2_3
chicago: Lewin, Mathieu, Elliott H. Lieb, and Robert Seiringer. “Universal Functionals
in Density Functional Theory.” In Density Functional Theory, edited by
Eric Cances and Gero Friesecke, 1st ed., 115–82. MAMOMO. Springer, 2023. https://doi.org/10.1007/978-3-031-22340-2_3.
ieee: M. Lewin, E. H. Lieb, and R. Seiringer, “Universal Functionals in Density
Functional Theory,” in Density Functional Theory, 1st ed., E. Cances and
G. Friesecke, Eds. Springer, 2023, pp. 115–182.
ista: 'Lewin M, Lieb EH, Seiringer R. 2023.Universal Functionals in Density Functional
Theory. In: Density Functional Theory. Mathematics and Molecular Modeling, , 115–182.'
mla: Lewin, Mathieu, et al. “Universal Functionals in Density Functional Theory.”
Density Functional Theory, edited by Eric Cances and Gero Friesecke, 1st
ed., Springer, 2023, pp. 115–82, doi:10.1007/978-3-031-22340-2_3.
short: M. Lewin, E.H. Lieb, R. Seiringer, in:, E. Cances, G. Friesecke (Eds.), Density
Functional Theory, 1st ed., Springer, 2023, pp. 115–182.
date_created: 2024-02-14T14:44:33Z
date_published: 2023-07-19T00:00:00Z
date_updated: 2024-02-20T08:33:06Z
day: '19'
department:
- _id: RoSe
doi: 10.1007/978-3-031-22340-2_3
edition: '1'
editor:
- first_name: Eric
full_name: Cances, Eric
last_name: Cances
- first_name: Gero
full_name: Friesecke, Gero
last_name: Friesecke
external_id:
arxiv:
- '1912.10424'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.1912.10424
month: '07'
oa: 1
oa_version: Preprint
page: 115-182
publication: Density Functional Theory
publication_identifier:
eisbn:
- '9783031223402'
isbn:
- '9783031223396'
issn:
- 3005-0286
publication_status: published
publisher: Springer
quality_controlled: '1'
series_title: MAMOMO
status: public
title: Universal Functionals in Density Functional Theory
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14993'
abstract:
- lang: eng
text: "Traditional top-down approaches for global health have historically failed
to achieve social progress (Hoffman et al., 2015; Hoffman & Røttingen, 2015).
Recently, however, a more holistic, multi-level approach termed One Health (OH)
(Osterhaus et al., 2020) is being adopted. Several sets of challenges have been
identified for the implementation of OH (dos S. Ribeiro et al., 2019), including
policy and funding, education and training, and multi-actor, multi-domain, and
multi-level collaborations. These exist despite the increasing accessibility to\r\nknowledge
and digital collaborative research tools through the internet. To address some
of these challenges, we propose a general framework for grassroots community-based
means of participatory research. Additionally, we present a specific roadmap to
create a Machine Learning for Global Health community in Africa. The proposed
framework aims to enable any small group of individuals with scarce resources
to build and sustain an online community within approximately two years. We provide
a discussion on the potential impact of the proposed framework for global health
research collaborations."
acknowledgement: "Houcemeddine Turki’s contributions to this final output have been
funded through the Adapting\r\nWikidata to support clinical practice using Data
Science, Semantic Web and Machine Learning\r\nproject, which is part of the Wikimedia
Research Fund maintained by the Wikimedia Foundation in San Francisco, California,
United States of America."
article_processing_charge: No
author:
- first_name: Christopher
full_name: Currin, Christopher
id: e8321fc5-3091-11eb-8a53-83f309a11ac9
last_name: Currin
orcid: 0000-0002-4809-5059
- first_name: Mercy Nyamewaa
full_name: Asiedu , Mercy Nyamewaa
last_name: 'Asiedu '
- first_name: Chris
full_name: Fourie, Chris
last_name: Fourie
- first_name: Benjamin
full_name: Rosman, Benjamin
last_name: Rosman
- first_name: Houcemeddine
full_name: Turki, Houcemeddine
last_name: Turki
- first_name: Atnafu
full_name: Lambebo Tonja, Atnafu
last_name: Lambebo Tonja
- first_name: Jade
full_name: Abbott, Jade
last_name: Abbott
- first_name: Marvellous
full_name: Ajala, Marvellous
last_name: Ajala
- first_name: Sadiq Adewale
full_name: Adedayo, Sadiq Adewale
last_name: Adedayo
- first_name: Chris Chinenye
full_name: Emezue, Chris Chinenye
last_name: Emezue
- first_name: Daphne
full_name: Machangara, Daphne
last_name: Machangara
citation:
ama: 'Currin C, Asiedu MN, Fourie C, et al. A framework for grassroots research
collaboration in machine learning and global health. In: 1st Workshop on Machine
Learning & Global Health. OpenReview; 2023.'
apa: 'Currin, C., Asiedu , M. N., Fourie, C., Rosman, B., Turki, H., Lambebo Tonja,
A., … Machangara, D. (2023). A framework for grassroots research collaboration
in machine learning and global health. In 1st Workshop on Machine Learning
& Global Health. Kigali, Rwanda: OpenReview.'
chicago: Currin, Christopher, Mercy Nyamewaa Asiedu , Chris Fourie, Benjamin Rosman,
Houcemeddine Turki, Atnafu Lambebo Tonja, Jade Abbott, et al. “A Framework for
Grassroots Research Collaboration in Machine Learning and Global Health.” In 1st
Workshop on Machine Learning & Global Health. OpenReview, 2023.
ieee: C. Currin et al., “A framework for grassroots research collaboration
in machine learning and global health,” in 1st Workshop on Machine Learning
& Global Health, Kigali, Rwanda, 2023.
ista: 'Currin C, Asiedu MN, Fourie C, Rosman B, Turki H, Lambebo Tonja A, Abbott
J, Ajala M, Adedayo SA, Emezue CC, Machangara D. 2023. A framework for grassroots
research collaboration in machine learning and global health. 1st Workshop on
Machine Learning & Global Health. ICLR: International Conference on Learning
Representations.'
mla: Currin, Christopher, et al. “A Framework for Grassroots Research Collaboration
in Machine Learning and Global Health.” 1st Workshop on Machine Learning &
Global Health, OpenReview, 2023.
short: C. Currin, M.N. Asiedu , C. Fourie, B. Rosman, H. Turki, A. Lambebo Tonja,
J. Abbott, M. Ajala, S.A. Adedayo, C.C. Emezue, D. Machangara, in:, 1st Workshop
on Machine Learning & Global Health, OpenReview, 2023.
conference:
end_date: 2023-05-05
location: Kigali, Rwanda
name: 'ICLR: International Conference on Learning Representations'
start_date: 2023-05-05
date_created: 2024-02-14T15:11:48Z
date_published: 2023-03-02T00:00:00Z
date_updated: 2026-06-18T17:42:25Z
day: '02'
ddc:
- '000'
department:
- _id: TiVo
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/forum?id=jHY_G91R880
month: '03'
oa: 1
oa_version: Published Version
publication: 1st Workshop on Machine Learning & Global Health
publication_status: published
publisher: OpenReview
quality_controlled: '1'
status: public
title: A framework for grassroots research collaboration in machine learning and global
health
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '14994'
abstract:
- lang: eng
text: This resource contains the artifacts for reproducing the experimental results
presented in the paper titled "A Flexible Toolchain for Symbolic Rabin Games under
Fair and Stochastic Uncertainties" that has been submitted in CAV 2023.
article_processing_charge: No
author:
- first_name: Rupak
full_name: Majumdar, Rupak
last_name: Majumdar
- first_name: Kaushik
full_name: Mallik, Kaushik
id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598
last_name: Mallik
orcid: 0000-0001-9864-7475
- first_name: Mateusz
full_name: Rychlicki, Mateusz
last_name: Rychlicki
- first_name: Anne-Kathrin
full_name: Schmuck, Anne-Kathrin
last_name: Schmuck
- first_name: Sadegh
full_name: Soudjani, Sadegh
last_name: Soudjani
citation:
ama: Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. A flexible toolchain
for symbolic rabin games under fair and stochastic uncertainties. 2023. doi:10.5281/ZENODO.7877790
apa: Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., & Soudjani, S.
(2023). A flexible toolchain for symbolic rabin games under fair and stochastic
uncertainties. Zenodo. https://doi.org/10.5281/ZENODO.7877790
chicago: Majumdar, Rupak, Kaushik Mallik, Mateusz Rychlicki, Anne-Kathrin Schmuck,
and Sadegh Soudjani. “A Flexible Toolchain for Symbolic Rabin Games under Fair
and Stochastic Uncertainties.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.7877790.
ieee: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible
toolchain for symbolic rabin games under fair and stochastic uncertainties.” Zenodo,
2023.
ista: Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. 2023. A flexible
toolchain for symbolic rabin games under fair and stochastic uncertainties, Zenodo,
10.5281/ZENODO.7877790.
mla: Majumdar, Rupak, et al. A Flexible Toolchain for Symbolic Rabin Games under
Fair and Stochastic Uncertainties. Zenodo, 2023, doi:10.5281/ZENODO.7877790.
short: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, S. Soudjani, (2023).
corr_author: '1'
date_created: 2024-02-14T15:13:00Z
date_published: 2023-04-28T00:00:00Z
date_updated: 2025-09-09T14:16:48Z
day: '28'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.5281/ZENODO.7877790
has_accepted_license: '1'
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.7877790
month: '04'
oa: 1
oa_version: Published Version
publisher: Zenodo
related_material:
record:
- id: '14758'
relation: used_in_publication
status: public
status: public
title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties
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: '2023'
...
---
OA_place: publisher
OA_type: gold
_id: '15027'
abstract:
- lang: eng
text: 'This data repository underpins the paper, published in PNAS (doi pending)
and bioarxiv (doi: https://doi.org/10.1101/2023.07.05.547777).'
article_processing_charge: No
author:
- first_name: Samo
full_name: Curk, Samo
id: 031eff0d-d481-11ee-8508-cd12a7a86e5b
last_name: Curk
orcid: 0000-0001-6160-9766
citation:
ama: Curk S. aggregation_data. 2023.
apa: Curk, S. (2023). aggregation_data. Figshare.
chicago: Curk, Samo. “Aggregation_data.” Figshare, 2023.
ieee: S. Curk, “aggregation_data.” Figshare, 2023.
ista: Curk S. 2023. aggregation_data, Figshare.
mla: Curk, Samo. Aggregation_data. Figshare, 2023.
short: S. Curk, (2023).
corr_author: '1'
date_created: 2024-02-26T08:37:57Z
date_published: 2023-12-13T00:00:00Z
date_updated: 2025-09-04T12:03:11Z
day: '13'
ddc:
- '570'
department:
- _id: AnSa
has_accepted_license: '1'
license: https://creativecommons.org/publicdomain/zero/1.0/
main_file_link:
- open_access: '1'
url: https://figshare.com/s/85798bba4ebc68d822ed
month: '12'
oa: 1
oa_version: Published Version
publisher: Figshare
related_material:
record:
- id: '15001'
relation: used_in_publication
status: public
status: public
title: aggregation_data
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: '2023'
...
---
_id: '15035'
abstract:
- lang: eng
text: "This artifact aims to reproduce experiments from the paper Monitoring Hyperproperties
With Prefix Transducers accepted at RV'23, and give further pointers to implementation
of prefix transducers.\r\nIt has two parts: a pre-compiled docker image and sources
that one can use to compile (locally or in docker) the software and run the experiments."
article_processing_charge: No
author:
- first_name: Marek
full_name: Chalupa, Marek
id: 87e34708-d6c6-11ec-9f5b-9391e7be2463
last_name: Chalupa
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Chalupa M, Henzinger TA. Monitoring hyperproperties with prefix transducers.
2023. doi:10.5281/ZENODO.8191723
apa: Chalupa, M., & Henzinger, T. A. (2023). Monitoring hyperproperties with
prefix transducers. Zenodo. https://doi.org/10.5281/ZENODO.8191723
chicago: Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with
Prefix Transducers.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.8191723.
ieee: M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers.”
Zenodo, 2023.
ista: Chalupa M, Henzinger TA. 2023. Monitoring hyperproperties with prefix transducers,
Zenodo, 10.5281/ZENODO.8191723.
mla: Chalupa, Marek, and Thomas A. Henzinger. Monitoring Hyperproperties with
Prefix Transducers. Zenodo, 2023, doi:10.5281/ZENODO.8191723.
short: M. Chalupa, T.A. Henzinger, (2023).
corr_author: '1'
date_created: 2024-02-28T07:34:34Z
date_published: 2023-07-28T00:00:00Z
date_updated: 2025-04-14T09:42:55Z
day: '28'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.5281/ZENODO.8191723
ec_funded: 1
has_accepted_license: '1'
main_file_link:
- open_access: '1'
url: https://doi.org/10.5281/zenodo.8191722
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publisher: Zenodo
related_material:
record:
- id: '14076'
relation: used_in_publication
status: public
status: public
title: Monitoring hyperproperties with prefix transducers
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: '2023'
...
---
_id: '15173'
abstract:
- lang: eng
text: 'We show that the number of linear spaces on a set of n points and the number
of rank-3 matroids on a ground set of size n are both of the form (cn+o(n))n2/6,
where c=e3√/2−3(1+3–√)/2. This is the final piece of the puzzle for enumerating
fixed-rank matroids at this level of accuracy: the numbers of rank-1 and rank-2
matroids on a ground set of size n have exact representations in terms of well-known
combinatorial functions, and it was recently proved by van der Hofstad, Pendavingh,
and van der Pol that for constant r≥4 there are (e1−rn+o(n))nr−1/r! rank-r matroids
on a ground set of size n. In our proof, we introduce a new approach for bounding
the number of clique decompositions of a complete graph, using quasirandomness
instead of the so-called entropy method that is common in this area.'
acknowledgement: "Sah and Sawhney were supported by NSF Graduate Research Fellowship
Program DGE-1745302. Sah was supported by the PD Soros Fellowship.\r\nWe thank Michael
Simkin for helpful comments on the manuscript. We thank Zach Hunter for\r\nseveral
corrections."
article_processing_charge: Yes
article_type: original
arxiv: 1
author:
- first_name: Matthew Alan
full_name: Kwan, Matthew Alan
id: 5fca0887-a1db-11eb-95d1-ca9d5e0453b3
last_name: Kwan
orcid: 0000-0002-4003-7567
- first_name: Ashwin
full_name: Sah, Ashwin
last_name: Sah
- first_name: Mehtaab
full_name: Sawhney, Mehtaab
last_name: Sawhney
citation:
ama: Kwan MA, Sah A, Sawhney M. Enumerating matroids and linear spaces. Comptes
Rendus Mathematique. 2023;361(G2):565-575. doi:10.5802/crmath.423
apa: Kwan, M. A., Sah, A., & Sawhney, M. (2023). Enumerating matroids and linear
spaces. Comptes Rendus Mathematique. Academie des Sciences. https://doi.org/10.5802/crmath.423
chicago: Kwan, Matthew Alan, Ashwin Sah, and Mehtaab Sawhney. “Enumerating Matroids
and Linear Spaces.” Comptes Rendus Mathematique. Academie des Sciences,
2023. https://doi.org/10.5802/crmath.423.
ieee: M. A. Kwan, A. Sah, and M. Sawhney, “Enumerating matroids and linear spaces,”
Comptes Rendus Mathematique, vol. 361, no. G2. Academie des Sciences, pp.
565–575, 2023.
ista: Kwan MA, Sah A, Sawhney M. 2023. Enumerating matroids and linear spaces. Comptes
Rendus Mathematique. 361(G2), 565–575.
mla: Kwan, Matthew Alan, et al. “Enumerating Matroids and Linear Spaces.” Comptes
Rendus Mathematique, vol. 361, no. G2, Academie des Sciences, 2023, pp. 565–75,
doi:10.5802/crmath.423.
short: M.A. Kwan, A. Sah, M. Sawhney, Comptes Rendus Mathematique 361 (2023) 565–575.
date_created: 2024-03-24T23:01:00Z
date_published: 2023-02-01T00:00:00Z
date_updated: 2025-09-09T14:26:32Z
day: '01'
ddc:
- '510'
department:
- _id: MaKw
doi: 10.5802/crmath.423
external_id:
arxiv:
- '2112.03788'
isi:
- '001167671400009'
file:
- access_level: open_access
checksum: d1d0e0a854a79ae95fb66d75d9117a68
content_type: application/pdf
creator: dernst
date_created: 2024-03-25T07:21:52Z
date_updated: 2024-03-25T07:21:52Z
file_id: '15174'
file_name: 2023_ComptesRendusMath_Kwan.pdf
file_size: 598097
relation: main_file
success: 1
file_date_updated: 2024-03-25T07:21:52Z
has_accepted_license: '1'
intvolume: ' 361'
isi: 1
issue: G2
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: 565-575
publication: Comptes Rendus Mathematique
publication_identifier:
eissn:
- 1778-3569
issn:
- 1631-073X
publication_status: published
publisher: Academie des Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Enumerating matroids and linear spaces
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: 361
year: '2023'
...
---
_id: '15292'
abstract:
- lang: eng
text: We present a rigid body animation technique which prevents solids from interpenetrating,
dissipates energy through friction, and propagates shocks through contacts. We
employ the Alternating Direction Method of Multipliers (ADMM) to couple non-smooth
Coulomb friction with impact propagation, allowing efficient and accurate non-smooth
dynamics along with a correct transmission of impacts through assemblies of rigid
bodies. We further extend our method to model adhesion, dynamic friction and lubricated
contact.
acknowledgement: We thank the anonymous reviewers and the members of the Visual Computing
Group at ISTA for their helpful comments. This research was supported by the Scientific
Service Units (SSU) of ISTA through resources provided by Scientific Computing,
and was funded in part by the European Union (ERC-2021-COG 101045083 CoDiNA)
article_processing_charge: No
author:
- first_name: Yi-Lu
full_name: Chen, Yi-Lu
id: 0b467602-dbcd-11ea-9d1d-ed480aa46b70
last_name: Chen
- first_name: Mickaël
full_name: Ly, Mickaël
id: 6340d7f0-b48d-11eb-b10d-b7487e71d9f1
last_name: Ly
- first_name: Christopher J
full_name: Wojtan, Christopher J
id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87
last_name: Wojtan
orcid: 0000-0001-6646-5546
citation:
ama: Chen Y-L, Ly M, Wojtan C. Unified Treatment of Contact, Friction and Shock-Propagation
in Rigid Body Animation. ACM; 2023. doi:10.1145/3606037.3606836
apa: 'Chen, Y.-L., Ly, M., & Wojtan, C. (2023). Unified treatment of contact,
friction and shock-propagation in rigid body animation. Proceedings of
the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. Los Angeles,
CA, United States: ACM. https://doi.org/10.1145/3606037.3606836'
chicago: Chen, Yi-Lu, Mickaël Ly, and Chris Wojtan. Unified Treatment of Contact,
Friction and Shock-Propagation in Rigid Body Animation. Proceedings of
the ACM SIGGRAPH/Eurographics Symposium on Computer Animation. ACM, 2023.
https://doi.org/10.1145/3606037.3606836.
ieee: Y.-L. Chen, M. Ly, and C. Wojtan, Unified treatment of contact, friction
and shock-propagation in rigid body animation. ACM, 2023.
ista: Chen Y-L, Ly M, Wojtan C. 2023. Unified treatment of contact, friction and
shock-propagation in rigid body animation, ACM,p.
mla: Chen, Yi-Lu, et al. “Unified Treatment of Contact, Friction and Shock-Propagation
in Rigid Body Animation.” Proceedings of the ACM SIGGRAPH/Eurographics Symposium
on Computer Animation, ACM, 2023, doi:10.1145/3606037.3606836.
short: Y.-L. Chen, M. Ly, C. Wojtan, Unified Treatment of Contact, Friction and
Shock-Propagation in Rigid Body Animation, ACM, 2023.
conference:
end_date: 2023-08-06
location: Los Angeles, CA, United States
name: 'SCA: Symposium on Computer Animation'
start_date: 2023-08-04
corr_author: '1'
date_created: 2024-04-03T14:57:23Z
date_published: 2023-08-01T00:00:00Z
date_updated: 2025-04-14T12:58:27Z
day: '01'
ddc:
- '005'
- '531'
department:
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- _id: ChWo
doi: 10.1145/3606037.3606836
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project:
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grant_number: '101045083'
name: Computational Discovery of Numerical Algorithms for Animation and Simulation
of Natural Phenomena
publication: Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation
publication_status: published
publisher: ACM
related_material:
record:
- id: '14748'
relation: other
status: public
status: public
title: Unified treatment of contact, friction and shock-propagation in rigid body
animation
type: conference_poster
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '17074'
abstract:
- lang: eng
text: We verify Bogoliubov's approximation for translation invariant Bose gases
in the mean field regime, i.e. we prove that the ground state energy EN is given
by EN=NeH+infσ(H)+oN→∞(1), where N is the number of particles, eH is the minimal
Hartree energy and H is the Bogoliubov Hamiltonian. As an intermediate result
we show the existence of approximate ground states ΨN, i.e. states satisfying
⟨HN⟩ΨN=EN+oN→∞(1), exhibiting complete Bose--Einstein condensation with respect
to one of the Hartree minimizers.
acknowledgement: "We are grateful to Rupert Frank for helpful discussions at an early
stage of this project.\r\nFunding from the European Union’s Horizon 2020 research
and innovation programme\r\nunder the ERC grant agreement No 694227 is acknowledged."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Morris
full_name: Brooks, Morris
id: B7ECF9FC-AA38-11E9-AC9A-0930E6697425
last_name: Brooks
orcid: 0000-0002-6249-0928
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: Brooks M, Seiringer R. Validity of Bogoliubov’s approximation fortranslation-invariant
Bose gases. Probability and Mathematical Physics. 2023;3(4):939-1000. doi:10.2140/pmp.2022.3.939
apa: Brooks, M., & Seiringer, R. (2023). Validity of Bogoliubov’s approximation
fortranslation-invariant Bose gases. Probability and Mathematical Physics.
Mathematical Sciences Publishers. https://doi.org/10.2140/pmp.2022.3.939
chicago: Brooks, Morris, and Robert Seiringer. “Validity of Bogoliubov’s Approximation
Fortranslation-Invariant Bose Gases.” Probability and Mathematical Physics.
Mathematical Sciences Publishers, 2023. https://doi.org/10.2140/pmp.2022.3.939.
ieee: M. Brooks and R. Seiringer, “Validity of Bogoliubov’s approximation fortranslation-invariant
Bose gases,” Probability and Mathematical Physics, vol. 3, no. 4. Mathematical
Sciences Publishers, pp. 939–1000, 2023.
ista: Brooks M, Seiringer R. 2023. Validity of Bogoliubov’s approximation fortranslation-invariant
Bose gases. Probability and Mathematical Physics. 3(4), 939–1000.
mla: Brooks, Morris, and Robert Seiringer. “Validity of Bogoliubov’s Approximation
Fortranslation-Invariant Bose Gases.” Probability and Mathematical Physics,
vol. 3, no. 4, Mathematical Sciences Publishers, 2023, pp. 939–1000, doi:10.2140/pmp.2022.3.939.
short: M. Brooks, R. Seiringer, Probability and Mathematical Physics 3 (2023) 939–1000.
corr_author: '1'
date_created: 2024-05-29T06:12:54Z
date_published: 2023-02-21T00:00:00Z
date_updated: 2025-04-14T07:26:59Z
day: '21'
department:
- _id: RoSe
doi: 10.2140/pmp.2022.3.939
ec_funded: 1
external_id:
arxiv:
- '2111.13864'
intvolume: ' 3'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2111.13864
month: '02'
oa: 1
oa_version: Preprint
page: 939-1000
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
publication: Probability and Mathematical Physics
publication_identifier:
eissn:
- 2690-1005
issn:
- 2690-0998
publication_status: published
publisher: Mathematical Sciences Publishers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Validity of Bogoliubov’s approximation fortranslation-invariant Bose gases
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 3
year: '2023'
...
---
_id: '17078'
abstract:
- lang: eng
text: For the emergence of life, the abiotic synthesis of RNA from its monomers
is a central step. We found that in alkaline, drying conditions in bulk and at
heated air‐water interfaces, 2′,3′‐cyclic nucleotides oligomerised without additional
catalyst, forming up to 10‐mers within a day. The oligomerisation proceeded at
a pH range of 7–12, at temperatures between 40–80 °C and was marginally enhanced
by K+ ions. Among the canonical ribonucleotides, cGMP oligomerised
most efficiently. Quantification was performed using HPLC coupled to ESI‐TOF by
fitting the isotope distribution to the mass spectra. Our study suggests a oligomerisation
mechanism where cGMP aids the incorporation of the relatively unreactive nucleotides
C, A and U. The 2′,3′‐cyclic ribonucleotides are byproducts of prebiotic phosphorylation,
nucleotide syntheses and RNA hydrolysis, indicating direct recycling pathways.
The simple reaction condition offers a plausible entry point for RNA to the evolution
of life on early Earth.
acknowledgement: We would like to thank Ulrich Gerland, Tobias Göppel, Joachim Rosenberger
and Bernhard Altaner for their helpful remarks and discussions; Thomas Matreux,
Alexandra Kühnlein, Noël Yeh Martin and Maximilian Weingart for comments on the
manuscript. The authors thank J. Kussmann (LMU Munich) for providing a development
version of the FermiONs++ program package. Financial support was provided by the
European Research Council (ERC Evotrap, grant no. 787356, the Simons Foundation
(grant no. 327125), the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
– Project-ID 364653263 – TRR 235 (CRC 235), the Deutsche Forschungsgemeinschaft
(DFG, German Research Foundation) under Germany's Excellence Strategy – EXC-2094
– 390783311, and the Center for NanoScience. Open Access funding enabled and organized
by Projekt DEAL.
article_number: e202200026
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Avinash Vicholous
full_name: Dass, Avinash Vicholous
last_name: Dass
- first_name: Sreekar
full_name: Wunnava, Sreekar
last_name: Wunnava
- first_name: Juliette
full_name: Langlais, Juliette
last_name: Langlais
- first_name: Beatriz
full_name: von der Esch, Beatriz
last_name: von der Esch
- first_name: Maik
full_name: Krusche, Maik
last_name: Krusche
- first_name: Lennard
full_name: Ufer, Lennard
last_name: Ufer
- first_name: Nico
full_name: Chrisam, Nico
last_name: Chrisam
- first_name: Romeo C. A.
full_name: Dubini, Romeo C. A.
last_name: Dubini
- first_name: Florian
full_name: Gartner, Florian
last_name: Gartner
- first_name: Severin
full_name: Angerpointner, Severin
last_name: Angerpointner
- first_name: Christina F.
full_name: Dirscherl, Christina F.
last_name: Dirscherl
- first_name: Petra
full_name: Rovo, Petra
id: c316e53f-b965-11eb-b128-bb26acc59c00
last_name: Rovo
orcid: 0000-0001-8729-7326
- first_name: Christof B.
full_name: Mast, Christof B.
last_name: Mast
- first_name: Judit E.
full_name: Šponer, Judit E.
last_name: Šponer
- first_name: Christian
full_name: Ochsenfeld, Christian
last_name: Ochsenfeld
- first_name: Erwin
full_name: Frey, Erwin
last_name: Frey
- first_name: Dieter
full_name: Braun, Dieter
last_name: Braun
citation:
ama: Dass AV, Wunnava S, Langlais J, et al. RNA oligomerisation without added catalyst
from 2′,3′‐cyclic nucleotides by drying at air-water interfaces. ChemSystemsChem.
2023;5(1). doi:10.1002/syst.202200026
apa: Dass, A. V., Wunnava, S., Langlais, J., von der Esch, B., Krusche, M., Ufer,
L., … Braun, D. (2023). RNA oligomerisation without added catalyst from 2′,3′‐cyclic
nucleotides by drying at air-water interfaces. ChemSystemsChem. Wiley.
https://doi.org/10.1002/syst.202200026
chicago: Dass, Avinash Vicholous, Sreekar Wunnava, Juliette Langlais, Beatriz von
der Esch, Maik Krusche, Lennard Ufer, Nico Chrisam, et al. “RNA Oligomerisation
without Added Catalyst from 2′,3′‐cyclic Nucleotides by Drying at Air-Water Interfaces.”
ChemSystemsChem. Wiley, 2023. https://doi.org/10.1002/syst.202200026.
ieee: A. V. Dass et al., “RNA oligomerisation without added catalyst from
2′,3′‐cyclic nucleotides by drying at air-water interfaces,” ChemSystemsChem,
vol. 5, no. 1. Wiley, 2023.
ista: Dass AV, Wunnava S, Langlais J, von der Esch B, Krusche M, Ufer L, Chrisam
N, Dubini RCA, Gartner F, Angerpointner S, Dirscherl CF, Rovo P, Mast CB, Šponer
JE, Ochsenfeld C, Frey E, Braun D. 2023. RNA oligomerisation without added catalyst
from 2′,3′‐cyclic nucleotides by drying at air-water interfaces. ChemSystemsChem.
5(1), e202200026.
mla: Dass, Avinash Vicholous, et al. “RNA Oligomerisation without Added Catalyst
from 2′,3′‐cyclic Nucleotides by Drying at Air-Water Interfaces.” ChemSystemsChem,
vol. 5, no. 1, e202200026, Wiley, 2023, doi:10.1002/syst.202200026.
short: A.V. Dass, S. Wunnava, J. Langlais, B. von der Esch, M. Krusche, L. Ufer,
N. Chrisam, R.C.A. Dubini, F. Gartner, S. Angerpointner, C.F. Dirscherl, P. Rovo,
C.B. Mast, J.E. Šponer, C. Ochsenfeld, E. Frey, D. Braun, ChemSystemsChem 5 (2023).
date_created: 2024-05-29T06:13:48Z
date_published: 2023-01-01T00:00:00Z
date_updated: 2025-07-10T11:51:15Z
day: '01'
ddc:
- '530'
department:
- _id: NMR
doi: 10.1002/syst.202200026
file:
- access_level: open_access
checksum: b1e78c60e371f87bdf43970f17d1cb0b
content_type: application/pdf
creator: dernst
date_created: 2024-07-31T11:20:58Z
date_updated: 2024-07-31T11:20:58Z
file_id: '17355'
file_name: 2023_ChemSystemsChem_Dass.pdf
file_size: 860679
relation: main_file
success: 1
file_date_updated: 2024-07-31T11:20:58Z
has_accepted_license: '1'
intvolume: ' 5'
issue: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '01'
oa: 1
oa_version: Published Version
publication: ChemSystemsChem
publication_identifier:
issn:
- 2570-4206
publication_status: published
publisher: Wiley
quality_controlled: '1'
scopus_import: '1'
status: public
title: RNA oligomerisation without added catalyst from 2′,3′‐cyclic nucleotides by
drying at air-water interfaces
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: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 5
year: '2023'
...