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Weakly-Supervised Disentanglement Without Compromises

Weakly-Supervised Disentanglement Without Compromises

7 February 2020
Francesco Locatello
Ben Poole
Gunnar Rätsch
Bernhard Schölkopf
Olivier Bachem
Michael Tschannen
    CoGe
    OOD
    DRL
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Papers citing "Weakly-Supervised Disentanglement Without Compromises"

50 / 69 papers shown
Title
Cross-Entropy Is All You Need To Invert the Data Generating Process
Cross-Entropy Is All You Need To Invert the Data Generating Process
Patrik Reizinger
Alice Bizeul
Attila Juhos
Julia E. Vogt
Randall Balestriero
Wieland Brendel
David Klindt
SSL
OOD
BDL
DRL
102
3
0
29 Oct 2024
Counterfactual Generative Modeling with Variational Causal Inference
Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu
Louie McConnell
Claudia Iriondo
CML
BDL
24
0
0
16 Oct 2024
Analyzing (In)Abilities of SAEs via Formal Languages
Analyzing (In)Abilities of SAEs via Formal Languages
Abhinav Menon
Manish Shrivastava
David M. Krueger
Ekdeep Singh Lubana
42
7
0
15 Oct 2024
Unsupervised Representation Learning from Sparse Transformation Analysis
Unsupervised Representation Learning from Sparse Transformation Analysis
Yue Song
Thomas Anderson Keller
Yisong Yue
Pietro Perona
Max Welling
DRL
29
0
0
07 Oct 2024
Smoke and Mirrors in Causal Downstream Tasks
Smoke and Mirrors in Causal Downstream Tasks
Riccardo Cadei
Lukas Lindorfer
Sylvia Cremer
Cordelia Schmid
Francesco Locatello
CML
33
3
0
27 May 2024
Learning Invariant Causal Mechanism from Vision-Language Models
Learning Invariant Causal Mechanism from Vision-Language Models
Zeen Song
Siyu Zhao
Xingyu Zhang
Jiangmeng Li
Changwen Zheng
Wenwen Qiang
CML
BDL
VLM
39
0
0
24 May 2024
Towards Controllable Time Series Generation
Towards Controllable Time Series Generation
Yifan Bao
Yihao Ang
Qiang Huang
Anthony K. H. Tung
Zhiyong Huang
DiffM
43
4
0
06 Mar 2024
On the Challenges and Opportunities in Generative AI
On the Challenges and Opportunities in Generative AI
Laura Manduchi
Kushagra Pandey
Robert Bamler
Ryan Cotterell
Sina Daubener
...
F. Wenzel
Frank Wood
Stephan Mandt
Vincent Fortuin
Vincent Fortuin
56
17
0
28 Feb 2024
Towards a Unified Framework of Contrastive Learning for Disentangled
  Representations
Towards a Unified Framework of Contrastive Learning for Disentangled Representations
Stefan Matthes
Zhiwei Han
Hao Shen
31
4
0
08 Nov 2023
Causal Representation Learning Made Identifiable by Grouping of
  Observational Variables
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
H. Morioka
Aapo Hyvarinen
OOD
CML
BDL
33
9
0
24 Oct 2023
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning
Disentangled Latent Spaces Facilitate Data-Driven Auxiliary Learning
Geri Skenderi
Luigi Capogrosso
Andrea Toaiari
Matteo Denitto
Franco Fummi
Simone Melzi
Marco Cristani
OOD
28
0
0
13 Oct 2023
Set Learning for Accurate and Calibrated Models
Set Learning for Accurate and Calibrated Models
Lukas Muttenthaler
Robert A. Vandermeulen
Qiuyi Zhang
Thomas Unterthiner
Klaus-Robert Muller
31
2
0
05 Jul 2023
Conditionally Invariant Representation Learning for Disentangling
  Cellular Heterogeneity
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
23
6
0
02 Jul 2023
Nonparametric Identifiability of Causal Representations from Unknown
  Interventions
Nonparametric Identifiability of Causal Representations from Unknown Interventions
Julius von Kügelgen
M. Besserve
Wendong Liang
Luigi Gresele
Armin Kekić
Elias Bareinboim
David M. Blei
Bernhard Schölkopf
CML
18
56
0
01 Jun 2023
Differentiable Random Partition Models
Differentiable Random Partition Models
Thomas M. Sutter
Alain Ryser
Joram Liebeskind
Julia E. Vogt
42
3
0
26 May 2023
Conditional Mutual Information for Disentangled Representations in
  Reinforcement Learning
Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
Mhairi Dunion
Trevor A. McInroe
K. Luck
Josiah P. Hanna
Stefano V. Albrecht
OOD
DRL
20
17
0
23 May 2023
A multimodal dynamical variational autoencoder for audiovisual speech
  representation learning
A multimodal dynamical variational autoencoder for audiovisual speech representation learning
Samir Sadok
Simon Leglaive
Laurent Girin
Xavier Alameda-Pineda
Renaud Séguier
23
11
0
05 May 2023
Correcting Flaws in Common Disentanglement Metrics
Correcting Flaws in Common Disentanglement Metrics
Louis Mahon
Lei Shah
Thomas Lukasiewicz
CoGe
DRL
32
3
0
05 Apr 2023
Simple Disentanglement of Style and Content in Visual Representations
Simple Disentanglement of Style and Content in Visual Representations
Lilian Ngweta
Subha Maity
Alex Gittens
Yuekai Sun
Mikhail Yurochkin
CoGe
DRL
24
7
0
20 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality
A Survey of Methods, Challenges and Perspectives in Causality
Gael Gendron
Michael Witbrock
Gillian Dobbie
OOD
AI4CE
CML
29
12
0
01 Feb 2023
Causal Triplet: An Open Challenge for Intervention-centric Causal
  Representation Learning
Causal Triplet: An Open Challenge for Intervention-centric Causal Representation Learning
Yuejiang Liu
Alexandre Alahi
Chris Russell
Max Horn
Dominik Zietlow
Bernhard Schölkopf
Francesco Locatello
CML
56
22
0
12 Jan 2023
Disentangled Representation Learning
Disentangled Representation Learning
Xin Eric Wang
Hong Chen
Siao Tang
Zihao Wu
Wenwu Zhu
DRL
32
78
0
21 Nov 2022
Distilling Representations from GAN Generator via Squeeze and Span
Distilling Representations from GAN Generator via Squeeze and Span
Yu Yang
Xiaotian Cheng
Chang-rui Liu
Hakan Bilen
Xiang Ji
GAN
29
0
0
06 Nov 2022
Robust Self-Supervised Learning with Lie Groups
Robust Self-Supervised Learning with Lie Groups
Mark Ibrahim
Diane Bouchacourt
Ari S. Morcos
SSL
OOD
38
6
0
24 Oct 2022
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent
  Factor Swapping
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent Factor Swapping
Jiageng Zhu
Hanchen Xie
Wael AbdAlmageed
SSL
CoGe
DRL
32
4
0
21 Sep 2022
A Causal Intervention Scheme for Semantic Segmentation of Quasi-periodic
  Cardiovascular Signals
A Causal Intervention Scheme for Semantic Segmentation of Quasi-periodic Cardiovascular Signals
Xingyao Wang
Yuwen Li
Hongxiang Gao
Xianghong Cheng
Jianqing Li
Chengyu Liu
17
6
0
19 Sep 2022
Weakly Supervised Invariant Representation Learning Via Disentangling
  Known and Unknown Nuisance Factors
Weakly Supervised Invariant Representation Learning Via Disentangling Known and Unknown Nuisance Factors
Jiageng Zhu
Hanchen Xie
Wael AbdAlmageed
24
1
0
15 Sep 2022
Assaying Out-Of-Distribution Generalization in Transfer Learning
Assaying Out-Of-Distribution Generalization in Transfer Learning
F. Wenzel
Andrea Dittadi
Peter V. Gehler
Carl-Johann Simon-Gabriel
Max Horn
...
Chris Russell
Thomas Brox
Bernt Schiele
Bernhard Schölkopf
Francesco Locatello
OOD
OODD
AAML
51
71
0
19 Jul 2022
Equivariant Representation Learning via Class-Pose Decomposition
Equivariant Representation Learning via Class-Pose Decomposition
G. Marchetti
Gustaf Tegnér
Anastasiia Varava
Danica Kragic
DRL
32
14
0
07 Jul 2022
GLANCE: Global to Local Architecture-Neutral Concept-based Explanations
GLANCE: Global to Local Architecture-Neutral Concept-based Explanations
Avinash Kori
Ben Glocker
Francesca Toni
27
6
0
05 Jul 2022
Invariant and Transportable Representations for Anti-Causal Domain
  Shifts
Invariant and Transportable Representations for Anti-Causal Domain Shifts
Yibo Jiang
Victor Veitch
OOD
123
32
0
04 Jul 2022
When are Post-hoc Conceptual Explanations Identifiable?
When are Post-hoc Conceptual Explanations Identifiable?
Tobias Leemann
Michael Kirchhof
Yao Rong
Enkelejda Kasneci
Gjergji Kasneci
50
10
0
28 Jun 2022
Identifiability of deep generative models without auxiliary information
Identifiability of deep generative models without auxiliary information
Bohdan Kivva
Goutham Rajendran
Pradeep Ravikumar
Bryon Aragam
DRL
23
48
0
20 Jun 2022
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Embrace the Gap: VAEs Perform Independent Mechanism Analysis
Patrik Reizinger
Luigi Gresele
Jack Brady
Julius von Kügelgen
Dominik Zietlow
Bernhard Schölkopf
Georg Martius
Wieland Brendel
M. Besserve
DRL
35
19
0
06 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse
  Mechanism Shift Hypothesis
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis
Ronan Perry
Julius von Kügelgen
Bernhard Schölkopf
41
48
0
04 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations
Weakly Supervised Representation Learning with Sparse Perturbations
Kartik Ahuja
Jason S. Hartford
Yoshua Bengio
SSL
35
58
0
02 Jun 2022
Gacs-Korner Common Information Variational Autoencoder
Gacs-Korner Common Information Variational Autoencoder
Michael Kleinman
Alessandro Achille
Stefano Soatto
J. Kao
CML
DRL
24
12
0
24 May 2022
Leveraging Relational Information for Learning Weakly Disentangled
  Representations
Leveraging Relational Information for Learning Weakly Disentangled Representations
Andrea Valenti
D. Bacciu
CoGe
DRL
27
5
0
20 May 2022
Accounting for the Sequential Nature of States to Learn Features for
  Reinforcement Learning
Accounting for the Sequential Nature of States to Learn Features for Reinforcement Learning
Nathan Michlo
Devon Jarvis
Richard Klein
Steven D. James
DRL
OffRL
11
0
0
12 May 2022
Disentangling A Single MR Modality
Disentangling A Single MR Modality
Lianrui Zuo
Yihao Liu
Yuan Xue
Shuo Han
M. Bilgel
Susan M. Resnick
Jerry L. Prince
A. Carass
19
14
0
10 May 2022
Lost in Latent Space: Disentangled Models and the Challenge of
  Combinatorial Generalisation
Lost in Latent Space: Disentangled Models and the Challenge of Combinatorial Generalisation
M. Montero
J. Bowers
Rui Ponte Costa
Casimir J. H. Ludwig
Gaurav Malhotra
DRL
CoGe
19
11
0
05 Apr 2022
Weakly supervised causal representation learning
Weakly supervised causal representation learning
Johann Brehmer
P. D. Haan
Phillip Lippe
Taco S. Cohen
OOD
CML
30
120
0
30 Mar 2022
Causality Inspired Representation Learning for Domain Generalization
Causality Inspired Representation Learning for Domain Generalization
Fangrui Lv
Jian Liang
Shuang Li
Bin Zang
Chi Harold Liu
Ziteng Wang
Di Liu
CML
OOD
30
160
0
27 Mar 2022
Symmetry-Based Representations for Artificial and Biological General
  Intelligence
Symmetry-Based Representations for Artificial and Biological General Intelligence
I. Higgins
S. Racanière
Danilo Jimenez Rezende
AI4CE
24
44
0
17 Mar 2022
Active Learning by Feature Mixing
Active Learning by Feature Mixing
Amin Parvaneh
Ehsan Abbasnejad
Damien Teney
Reza Haffari
A. Hengel
Javen Qinfeng Shi
29
89
0
14 Mar 2022
Learning Group Importance using the Differentiable Hypergeometric
  Distribution
Learning Group Importance using the Differentiable Hypergeometric Distribution
Thomas M. Sutter
Laura Manduchi
Alain Ryser
Julia E. Vogt
41
7
0
03 Mar 2022
On Pitfalls of Identifiability in Unsupervised Learning. A Note on:
  "Desiderata for Representation Learning: A Causal Perspective"
On Pitfalls of Identifiability in Unsupervised Learning. A Note on: "Desiderata for Representation Learning: A Causal Perspective"
Shubhangi Ghosh
Luigi Gresele
Julius von Kügelgen
M. Besserve
Bernhard Schölkopf
CML
17
0
0
14 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences
CITRIS: Causal Identifiability from Temporal Intervened Sequences
Phillip Lippe
Sara Magliacane
Sindy Lowe
Yuki M. Asano
Taco S. Cohen
E. Gavves
CML
43
101
0
07 Feb 2022
Right for the Right Latent Factors: Debiasing Generative Models via
  Disentanglement
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement
Xiaoting Shao
Karl Stelzner
Kristian Kersting
CML
DRL
22
3
0
01 Feb 2022
Disentanglement and Generalization Under Correlation Shifts
Disentanglement and Generalization Under Correlation Shifts
Christina M. Funke
Paul Vicol
Kuan-Chieh Jackson Wang
Matthias Kümmerer
R. Zemel
Matthias Bethge
OOD
33
7
0
29 Dec 2021
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