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Variational Autoencoders and Nonlinear ICA: A Unifying Framework
v1v2v3v4 (latest)

Variational Autoencoders and Nonlinear ICA: A Unifying Framework

International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
10 July 2019
Ilyes Khemakhem
Diederik P. Kingma
Ricardo Pio Monti
Aapo Hyvarinen
    OOD
ArXiv (abs)PDFHTML

Papers citing "Variational Autoencoders and Nonlinear ICA: A Unifying Framework"

50 / 402 papers shown
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
Yichao Cai
Yuhang Liu
Erdun Gao
Tianjiao Jiang
Zhen Zhang
Anton van den Hengel
Javen Qinfeng Shi
629
0
0
14 Apr 2025
Domain Adaptation Under MNAR Missingness
Domain Adaptation Under MNAR Missingness
Tyrel Stokes
Hyungrok Do
Saul Blecker
Rumi Chunara
Samrachana Adhikari
OOD
228
1
0
01 Apr 2025
Nonparametric Factor Analysis and Beyond
Nonparametric Factor Analysis and BeyondInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Yujia Zheng
Yang Liu
Jiaxiong Yao
Yingyao Hu
Jianchao Tan
CML
216
2
0
21 Mar 2025
Robustness of Nonlinear Representation Learning
Robustness of Nonlinear Representation LearningInternational Conference on Machine Learning (ICML), 2025
Simon Buchholz
Bernhard Schölkopf
OOD
862
6
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
1.1K
5
0
12 Mar 2025
Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent Spaces
Escaping Plato's Cave: Towards the Alignment of 3D and Text Latent SpacesComputer Vision and Pattern Recognition (CVPR), 2025
Souhail Hadgi
Luca Moschella
Andrea Santilli
Diego Gomez
Qixing Huang
Emanuele Rodolà
Simone Melzi
M. Ovsjanikov
268
1
0
07 Mar 2025
Time-varying Factor Augmented Vector Autoregression with Grouped Sparse Autoencoder
Yiyong Luo
Brooks Paige
Jim Griffin
CML
265
2
0
06 Mar 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System
Sanity Checking Causal Representation Learning on a Simple Real-World System
Juan L. Gamella
Simon Bing
Jakob Runge
CML
483
2
0
27 Feb 2025
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption
Causal Effect Estimation under Networked Interference without Networked Unconfoundedness Assumption
Weilin Chen
Ruichu Cai
Jie Qiao
Yuguang Yan
José Miguel Hernández-Lobato
CML
342
1
0
27 Feb 2025
Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization
Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization
Grace Guinan
Addison Salvador
Michelle A. Smeaton
Andrew Glaws
Hilary Egan
Brian C. Wyatt
Babak Anasori
K. Fiedler
M. Olszta
Steven Spurgeon
329
5
0
25 Feb 2025
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series ForecastingAAAI Conference on Artificial Intelligence (AAAI), 2025
Ruichu Cai
Haiqin Huang
Zhifang Jiang
Zijian Li
Changze Zhou
Yuequn Liu
Yuming Liu
Zijian Li
AI4TSCML
316
3
0
18 Feb 2025
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Archetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Thomas Fel
Ekdeep Singh Lubana
Jacob S. Prince
M. Kowal
Victor Boutin
Isabel Papadimitriou
Binxu Wang
Martin Wattenberg
Demba Ba
Talia Konkle
304
28
0
18 Feb 2025
Time-series attribution maps with regularized contrastive learning
Time-series attribution maps with regularized contrastive learningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Steffen Schneider
Rodrigo González Laiz
Anastasiia Filippova
Markus Frey
Mackenzie W. Mathis
BDLFAttCMLAI4TS
288
5
0
17 Feb 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
Samuele Bortolotti
Emanuele Marconato
Paolo Morettin
Baptiste Caramiaux
Stefano Teso
407
8
0
16 Feb 2025
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions
H. Fokkema
T. Erven
Sara Magliacane
489
3
0
10 Feb 2025
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
A Revisit of Total Correlation in Disentangled Variational Auto-Encoder with Partial Disentanglement
Chengrui Li
Yunmiao Wang
Yule Wang
Weihan Li
Dieter Jaeger
Anqi Wu
CoGeDRL
316
3
0
04 Feb 2025
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis
Minghao Fu
Zhen Zhang
Zijian Li
Yujia Zheng
Ignavier Ng
Guangyi Chen
Yingyao Hu
Kun Zhang
CML
336
3
0
21 Jan 2025
Towards Understanding Extrapolation: a Causal Lens
Towards Understanding Extrapolation: a Causal LensNeural Information Processing Systems (NeurIPS), 2025
Lingjing Kong
Guangyi Chen
P. Stojanov
Haoyang Li
Eric P. Xing
Kun Zhang
673
4
0
17 Jan 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based ModelsNeural Information Processing Systems (NeurIPS), 2024
Daniela de Albuquerque
John Pearson
DiffM
451
1
0
03 Jan 2025
Disentangled Representation Learning for Causal Inference with
  Instruments
Disentangled Representation Learning for Causal Inference with InstrumentsIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
Debo Cheng
Jiuyong Li
Lin Liu
Ziqi Xu
Weijia Zhang
Qingbin Liu
T. Le
OODCML
233
8
0
05 Dec 2024
Hierarchical VAE with a Diffusion-based VampPrior
Hierarchical VAE with a Diffusion-based VampPrior
Anna Kuzina
Jakub M. Tomczak
DiffMTPMBDL
365
3
0
02 Dec 2024
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 ModelingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Emanuele Marconato
Sébastien Lachapelle
Sebastian Weichwald
Luigi Gresele
377
6
0
30 Oct 2024
Learning Identifiable Factorized Causal Representations of Cellular
  Responses
Learning Identifiable Factorized Causal Representations of Cellular ResponsesNeural Information Processing Systems (NeurIPS), 2024
Haiyi Mao
Romain Lopez
Kai Liu
Jan-Christian Huetter
David Richmond
Panayiotis Benos
Lin Qiu
CML
272
5
0
29 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 ProcessInternational Conference on Learning Representations (ICLR), 2024
Patrik Reizinger
Alice Bizeul
Attila Juhos
Julia E. Vogt
Randall Balestriero
Wieland Brendel
David Klindt
SSLOODBDLDRL
579
17
0
29 Oct 2024
Your Image is Secretly the Last Frame of a Pseudo Video
Your Image is Secretly the Last Frame of a Pseudo Video
Wenlong Chen
Wenlin Chen
Lapo Rastrelli
Yingzhen Li
DiffMVGen
378
0
0
26 Oct 2024
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
Language Agents Meet Causality -- Bridging LLMs and Causal World Models
John Gkountouras
Matthias Lindemann
Phillip Lippe
E. Gavves
Ivan Titov
LRM
263
5
0
25 Oct 2024
Interpretable Representation Learning from Videos using Nonlinear Priors
Interpretable Representation Learning from Videos using Nonlinear PriorsBritish Machine Vision Conference (BMVC), 2024
Marian Longa
Joao F. Henriques
CMLDRL
236
0
0
24 Oct 2024
Self-supervised contrastive learning performs non-linear system identification
Self-supervised contrastive learning performs non-linear system identificationInternational Conference on Learning Representations (ICLR), 2024
Rodrigo González Laiz
Tobias Schmidt
Steffen Schneider
SSL
291
4
0
18 Oct 2024
Constraint Decoupled Latent Diffusion for Protein Backmapping
Constraint Decoupled Latent Diffusion for Protein Backmapping
Xu Han
Yuancheng Sun
Kai Chen
Kang Liu
Qiwei Ye
Qiwei Ye
DiffMAI4CE
316
1
0
17 Oct 2024
Counterfactual Generative Modeling with Variational Causal Inference
Counterfactual Generative Modeling with Variational Causal InferenceInternational Conference on Learning Representations (ICLR), 2024
Yulun Wu
Louie McConnell
Claudia Iriondo
CMLBDL
570
9
0
16 Oct 2024
Causal Representation Learning in Temporal Data via Single-Parent
  Decoding
Causal Representation Learning in Temporal Data via Single-Parent Decoding
Philippe Brouillard
Sébastien Lachapelle
Julia Kaltenborn
Yaniv Gurwicz
Dhanya Sridhar
Alexandre Drouin
Peer Nowack
Jakob Runge
David Rolnick
CML
233
8
0
09 Oct 2024
Rethinking Fair Representation Learning for Performance-Sensitive Tasks
Rethinking Fair Representation Learning for Performance-Sensitive TasksInternational Conference on Learning Representations (ICLR), 2024
Charles Jones
Fabio De Sousa Ribeiro
Mélanie Roschewitz
Daniel Coelho De Castro
Ben Glocker
FaMLOODCML
659
5
0
05 Oct 2024
Disentangled Representation Learning for Parametric Partial Differential
  Equations
Disentangled Representation Learning for Parametric Partial Differential Equations
Ning Liu
Lu Zhang
Tian Gao
Yue Yu
DRLAI4CE
245
3
0
03 Oct 2024
Mitigating Propensity Bias of Large Language Models for Recommender Systems
Mitigating Propensity Bias of Large Language Models for Recommender Systems
Guixian Zhang
Guan Yuan
Debo Cheng
Lin Liu
Jiuyong Li
Shichao Zhang
303
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30 Sep 2024
Embed and Emulate: Contrastive representations for simulation-based
  inference
Embed and Emulate: Contrastive representations for simulation-based inference
Ruoxi Jiang
Peter Y. Lu
Rebecca Willett
225
1
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27 Sep 2024
Latent mixed-effect models for high-dimensional longitudinal data
Latent mixed-effect models for high-dimensional longitudinal data
Priscilla Ong
Manuel Haußmann
Otto Lönnroth
Harri Lähdesmäki
154
3
0
17 Sep 2024
Celcomen: spatial causal disentanglement for single-cell and tissue
  perturbation modeling
Celcomen: spatial causal disentanglement for single-cell and tissue perturbation modeling
Stathis Megas
Daniel G. Chen
K. Polański
Moshe Eliasof
Carola-Bibiane Schönlieb
Sarah Teichmann
184
5
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09 Sep 2024
A method to benchmark high-dimensional process drift detection
A method to benchmark high-dimensional process drift detectionJournal of Intelligent Manufacturing (J Intell Manuf), 2024
Edgar Wolf
Tobias Windisch
AI4TS
168
0
0
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Causal Temporal Representation Learning with Nonstationary Sparse
  Transition
Causal Temporal Representation Learning with Nonstationary Sparse TransitionNeural Information Processing Systems (NeurIPS), 2024
Xiangchen Song
Zijian Li
Guangyi Chen
Yujia Zheng
Yewen Fan
Xinshuai Dong
Kun Zhang
CML
202
8
0
05 Sep 2024
Rethinking State Disentanglement in Causal Reinforcement Learning
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao
Zhen Zhang
Panpan Cai
Yuhang Liu
Jinan Zou
Ehsan Abbasnejad
Biwei Huang
Biwei Huang
Anton van den Hengel
Javen Qinfeng Shi
CML
154
0
0
24 Aug 2024
Causal Effect Estimation using identifiable Variational AutoEncoder with
  Latent Confounders and Post-Treatment Variables
Causal Effect Estimation using identifiable Variational AutoEncoder with Latent Confounders and Post-Treatment Variables
Yang Xie
Ziqi Xu
Debo Cheng
Jiuyong Li
Lin Liu
Yinghao Zhang
Zaiwen Feng
CMLBDL
169
1
0
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Continual Learning of Nonlinear Independent Representations
Continual Learning of Nonlinear Independent Representations
Boyang Sun
Ignavier Ng
Guangyi Chen
Yifan Shen
Qirong Ho
Kun Zhang
OODCML
270
0
0
11 Aug 2024
Controlling for discrete unmeasured confounding in nonlinear causal
  models
Controlling for discrete unmeasured confounding in nonlinear causal modelsCLEaR (CLEaR), 2024
Patrick Burauel
Frederick Eberhardt
Michel Besserve
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147
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0
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Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive RepresentationsInternational Conference on Learning Representations (ICLR), 2024
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Erdun Gao
Fan Feng
Xinyue Wang
Shikui Tu
Lei Xu
CMLOODTTA
633
1
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30 Jul 2024
Linear causal disentanglement via higher-order cumulants
Linear causal disentanglement via higher-order cumulants
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Chiara Meroni
A. Seigal
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208
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Robust Policy Learning for Multi-UAV Collision Avoidance with Causal
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Gaofei Han
Zihao Xia
Boxi Wang
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Zhun Fan
146
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Uniform Transformation: Refining Latent Representation in Variational
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C. S. G. Lee
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268
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Disentangled Representations for Causal Cognition
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264
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HarmonICA: Neural non-stationarity correction and source separation for
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