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Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive
  Learning

Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

22 May 2018
Aapo Hyvarinen
Hiroaki Sasaki
Richard Turner
    OOD
    CML
ArXivPDFHTML

Papers citing "Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning"

50 / 83 papers shown
Title
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism
Ruichu Cai
Kaitao Zheng
Junxian Huang
Zijian Li
Zhengming Chen
Boyan Xu
Zhifeng Hao
AI4TS
CML
33
0
0
12 May 2025
Multi-Domain Causal Discovery in Bijective Causal Models
Multi-Domain Causal Discovery in Bijective Causal Models
Kasra Jalaldoust
Saber Salehkaleybar
Negar Kiyavash
CML
76
0
0
30 Apr 2025
Robustness of Nonlinear Representation Learning
Robustness of Nonlinear Representation Learning
Simon Buchholz
Bernhard Schölkopf
OOD
221
3
0
19 Mar 2025
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?
Yuhang Liu
Dong Gong
Erdun Gao
Zhen Zhang
Zhen Zhang
Biwei Huang
Anton van den Hengel
Javen Qinfeng Shi
Javen Qinfeng Shi
226
0
0
12 Mar 2025
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
H. Fokkema
T. Erven
Sara Magliacane
70
1
0
10 Feb 2025
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling
All or None: Identifiable Linear Properties of Next-token Predictors in Language Modeling
Emanuele Marconato
Sébastien Lachapelle
Sebastian Weichwald
Luigi Gresele
69
3
0
30 Oct 2024
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
27
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
50
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
38
0
0
07 Oct 2024
Learning Discrete Concepts in Latent Hierarchical Models
Learning Discrete Concepts in Latent Hierarchical Models
Lingjing Kong
Guan-Hong Chen
Erdun Gao
Eric P. Xing
Yuejie Chi
Kun Zhang
52
4
0
01 Jun 2024
Sparsity regularization via tree-structured environments for
  disentangled representations
Sparsity regularization via tree-structured environments for disentangled representations
Elliot Layne
Jason S. Hartford
Sébastien Lachapelle
Mathieu Blanchette
Dhanya Sridhar
OOD
CML
33
0
0
30 May 2024
Separating common from salient patterns with Contrastive Representation
  Learning
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset
Edouard Duchesnay
Antoine Grigis
Pietro Gori
SSL
DRL
46
1
0
19 Feb 2024
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
Yuhang Liu
Zhen Zhang
Dong Gong
Erdun Gao
Biwei Huang
Anton Van Den Hengel
Kun Zhang
Javen Qinfeng Shi
Javen Qinfeng Shi
52
5
0
09 Feb 2024
Towards Identifiable Unsupervised Domain Translation: A Diversified
  Distribution Matching Approach
Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
Sagar Shrestha
Xiao Fu
23
3
0
18 Jan 2024
Step and Smooth Decompositions as Topological Clustering
Step and Smooth Decompositions as Topological Clustering
Luciano Vinas
Arash A. Amini
24
0
0
09 Nov 2023
Identifying Semantic Component for Robust Molecular Property Prediction
Identifying Semantic Component for Robust Molecular Property Prediction
Zijian Li
Zunhong Xu
Ruichu Cai
Zhenhui Yang
Yuguang Yan
Zhifeng Hao
Guan-Hong Chen
Kun Zhang
25
9
0
08 Nov 2023
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
39
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
Subspace Identification for Multi-Source Domain Adaptation
Subspace Identification for Multi-Source Domain Adaptation
Zijian Li
Ruichu Cai
Guan-Hong Chen
Boyang Sun
Zhifeng Hao
Kun Zhang
36
33
0
07 Oct 2023
Identifiability Matters: Revealing the Hidden Recoverable Condition in
  Unbiased Learning to Rank
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
Mouxiang Chen
Chenghao Liu
Zemin Liu
Zhuo Li
Jianling Sun
CML
32
2
0
27 Sep 2023
Kernel Single Proxy Control for Deterministic Confounding
Kernel Single Proxy Control for Deterministic Confounding
Liyuan Xu
Arthur Gretton
CML
28
2
0
08 Aug 2023
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning:
  A Survey
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey
Gabriele Lagani
Fabrizio Falchi
Claudio Gennaro
Giuseppe Amato
AAML
45
6
0
30 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
31
6
0
02 Jul 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models
High Fidelity Image Counterfactuals with Probabilistic Causal Models
Fabio De Sousa Ribeiro
Tian Xia
M. Monteiro
Nick Pawlowski
Ben Glocker
DiffM
40
36
0
27 Jun 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent
  Causal Models
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
Zeyu Zhou
Ruqi Bai
Sean Kulinski
Murat Kocaoglu
David I. Inouye
CML
26
1
0
20 Jun 2023
Partial Identifiability for Domain Adaptation
Partial Identifiability for Domain Adaptation
Lingjing Kong
Shaoan Xie
Weiran Yao
Yujia Zheng
Guan-Hong Chen
P. Stojanov
Victor Akinwande
Kun Zhang
53
9
0
10 Jun 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
23
57
0
01 Jun 2023
Towards understanding neural collapse in supervised contrastive learning
  with the information bottleneck method
Towards understanding neural collapse in supervised contrastive learning with the information bottleneck method
Siwei Wang
S. Palmer
35
2
0
19 May 2023
Identifiability of latent-variable and structural-equation models: from
  linear to nonlinear
Identifiability of latent-variable and structural-equation models: from linear to nonlinear
Aapo Hyvarinen
Ilyes Khemakhem
R. Monti
CML
50
41
0
06 Feb 2023
Emerging Synergies in Causality and Deep Generative Models: A Survey
Emerging Synergies in Causality and Deep Generative Models: A Survey
Guanglin Zhou
Shaoan Xie
Guang-Yuan Hao
Shiming Chen
Erdun Gao
Xiwei Xu
Chen Wang
Liming Zhu
Lina Yao
Kun Zhang
AI4CE
57
11
0
29 Jan 2023
Linear Causal Disentanglement via Interventions
Linear Causal Disentanglement via Interventions
C. Squires
A. Seigal
Salil Bhate
Caroline Uhler
CML
29
66
0
29 Nov 2022
Disentangled Representation Learning
Disentangled Representation Learning
Xin Eric Wang
Hong Chen
Siao Tang
Zihao Wu
Wenwu Zhu
DRL
39
78
0
21 Nov 2022
Temporally Disentangled Representation Learning
Temporally Disentangled Representation Learning
Weiran Yao
Guangyi Chen
Kun Zhang
CML
BDL
OOD
32
48
0
24 Oct 2022
Universal hidden monotonic trend estimation with contrastive learning
Universal hidden monotonic trend estimation with contrastive learning
Edouard Pineau
S. Razakarivony
Mauricio Gonzalez
A. Schrapffer
33
0
0
18 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs
CLEAR: Generative Counterfactual Explanations on Graphs
Jing Ma
Ruocheng Guo
Saumitra Mishra
Aidong Zhang
Jundong Li
CML
OOD
40
54
0
16 Oct 2022
Provable Subspace Identification Under Post-Nonlinear Mixtures
Provable Subspace Identification Under Post-Nonlinear Mixtures
Qi Lyu
Xiao Fu
CoGe
29
0
0
14 Oct 2022
Multi-View Independent Component Analysis with Shared and Individual
  Sources
Multi-View Independent Component Analysis with Shared and Individual Sources
T. Pandeva
Patrick Forré
CML
15
5
0
05 Oct 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
54
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
26
49
0
20 Jun 2022
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
On the Identifiability of Nonlinear ICA: Sparsity and Beyond
Yujia Zheng
Ignavier Ng
Kun Zhang
CML
26
59
0
15 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
37
19
0
06 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
Learnable latent embeddings for joint behavioral and neural analysis
Learnable latent embeddings for joint behavioral and neural analysis
Steffen Schneider
Jin Hwa Lee
Mackenzie W. Mathis
23
212
0
01 Apr 2022
From Statistical to Causal Learning
From Statistical to Causal Learning
Bernhard Schölkopf
Julius von Kügelgen
CML
32
45
0
01 Apr 2022
Language modeling via stochastic processes
Language modeling via stochastic processes
Rose E. Wang
Esin Durmus
Noah D. Goodman
Tatsunori Hashimoto
BDL
AI4TS
40
24
0
21 Mar 2022
Mixing Up Contrastive Learning: Self-Supervised Representation Learning
  for Time Series
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series
Kristoffer Wickstrøm
Michael C. Kampffmeyer
Karl Øyvind Mikalsen
Robert Jenssen
SSL
AI4TS
20
94
0
17 Mar 2022
Stochastic Perturbations of Tabular Features for Non-Deterministic
  Inference with Automunge
Stochastic Perturbations of Tabular Features for Non-Deterministic Inference with Automunge
Nicholas J. Teague
AAML
33
1
0
18 Feb 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
19
0
0
14 Feb 2022
CITRIS: Causal Identifiability from Temporal Intervened Sequences
CITRIS: Causal Identifiability from Temporal Intervened Sequences
Phillip Lippe
Sara Magliacane
Sindy Löwe
Yuki M. Asano
Taco S. Cohen
E. Gavves
CML
46
102
0
07 Feb 2022
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