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1907.04809
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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
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Papers citing
"Variational Autoencoders and Nonlinear ICA: A Unifying Framework"
50 / 402 papers shown
Identifying Semantic Component for Robust Molecular Property Prediction
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Zunhong Xu
Ruichu Cai
Zhenhui Yang
Yuguang Yan
Zhifeng Hao
Guan-Hong Chen
Kun Zhang
213
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Towards a Unified Framework of Contrastive Learning for Disentangled Representations
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Zhiwei Han
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265
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08 Nov 2023
The Linear Representation Hypothesis and the Geometry of Large Language Models
International Conference on Machine Learning (ICML), 2023
Kiho Park
Yo Joong Choe
Victor Veitch
LLMSV
MILM
471
323
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07 Nov 2023
Neural Structure Learning with Stochastic Differential Equations
International Conference on Learning Representations (ICLR), 2023
Benjie Wang
Joel Jennings
Wenbo Gong
CML
AI4TS
218
9
0
06 Nov 2023
Estimating treatment effects from single-arm trials via latent-variable modeling
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Manuel Haussmann
Tran Minh Son Le
Viivi Halla-aho
Samu Kurki
Jussi Leinonen
Miika Koskinen
Samuel Kaski
Harri Lähdesmäki
CML
298
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0
06 Nov 2023
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
CLEaR (CLEaR), 2023
Simon Bing
Urmi Ninad
Jonas Wahl
Jakob Runge
CML
380
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0
05 Nov 2023
Generalizing Nonlinear ICA Beyond Structural Sparsity
Neural Information Processing Systems (NeurIPS), 2023
Yujia Zheng
Kun Zhang
CML
189
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0
01 Nov 2023
Object-centric architectures enable efficient causal representation learning
International Conference on Learning Representations (ICLR), 2023
Amin Mansouri
Jason S. Hartford
Yan Zhang
Yoshua Bengio
CML
OCL
OOD
282
25
0
29 Oct 2023
Temporally Disentangled Representation Learning under Unknown Nonstationarity
Neural Information Processing Systems (NeurIPS), 2023
Xiangchen Song
Weiran Yao
Yewen Fan
Xinshuai Dong
Guan-Hong Chen
Juan Carlos Niebles
Eric P. Xing
Kun Zhang
CML
OOD
328
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0
28 Oct 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables
International Conference on Machine Learning (ICML), 2023
H. Morioka
Aapo Hyvarinen
OOD
CML
BDL
464
20
0
24 Oct 2023
Identifiable Latent Polynomial Causal Models Through the Lens of Change
International Conference on Learning Representations (ICLR), 2023
Yuhang Liu
Zhen Zhang
Dong Gong
Biwei Huang
Erdun Gao
Anton Van Den Hengel
Kun Zhang
Javen Qinfeng Shi
254
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24 Oct 2023
General Identifiability and Achievability for Causal Representation Learning
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Burak Varici
Emre Acartürk
Karthikeyan Shanmugam
A. Tajer
CML
366
26
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24 Oct 2023
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling
Aneesh Komanduri
Xintao Wu
Yongkai Wu
Feng Chen
CML
OOD
464
23
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17 Oct 2023
High Dimensional Causal Inference with Variational Backdoor Adjustment
Daniel Israel
Aditya Grover
Karen Ullrich
CML
178
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09 Oct 2023
Provable Compositional Generalization for Object-Centric Learning
International Conference on Learning Representations (ICLR), 2023
Thaddäus Wiedemer
Jack Brady
Alexander Panfilov
Attila Juhos
Matthias Bethge
Wieland Brendel
OCL
320
34
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09 Oct 2023
The Emergence of Reproducibility and Generalizability in Diffusion Models
Huijie Zhang
Jinfan Zhou
Yifu Lu
Minzhe Guo
Peng Wang
Liyue Shen
Qing Qu
DiffM
302
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0
08 Oct 2023
Subspace Identification for Multi-Source Domain Adaptation
Neural Information Processing Systems (NeurIPS), 2023
Zijian Li
Ruichu Cai
Guan-Hong Chen
Boyang Sun
Zijian Li
Kun Zhang
262
50
0
07 Oct 2023
Offline Imitation Learning with Variational Counterfactual Reasoning
Neural Information Processing Systems (NeurIPS), 2023
Bowei He
Zexu Sun
Jinxin Liu
Shuai Zhang
Xu Chen
Chen Ma
OffRL
269
10
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07 Oct 2023
Identifying Representations for Intervention Extrapolation
International Conference on Learning Representations (ICLR), 2023
Sorawit Saengkyongam
Ezgi Ozyilkan
Pradeep Ravikumar
Niklas Pfister
Jonas Peters
CML
OOD
249
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06 Oct 2023
Multi-Domain Causal Representation Learning via Weak Distributional Invariances
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Kartik Ahuja
Amin Mansouri
Yixin Wang
CML
OOD
387
16
0
04 Oct 2023
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
International Conference on Learning Representations (ICLR), 2023
Ziqi Xu
Debo Cheng
Jiuyong Li
Jixue Liu
Lin Liu
Kui Yu
CML
184
20
0
03 Oct 2023
TP2O: Creative Text Pair-to-Object Generation using Balance Swap-Sampling
European Conference on Computer Vision (ECCV), 2023
Jun Li
Zedong Zhang
Zhiqiang Wang
DiffM
251
16
0
03 Oct 2023
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank
International Conference on Machine Learning (ICML), 2023
Mouxiang Chen
Chenghao Liu
Zemin Liu
Zhuo Li
Jianling Sun
CML
288
4
0
27 Sep 2023
Word Embedding with Neural Probabilistic Prior
SDM (SDM), 2023
Shaogang Ren
Dingcheng Li
P. Li
BDL
145
0
0
21 Sep 2023
Context is Environment
International Conference on Learning Representations (ICLR), 2023
Sharut Gupta
Stefanie Jegelka
David Lopez-Paz
Kartik Ahuja
230
0
0
18 Sep 2023
Interpretability is in the Mind of the Beholder: A Causal Framework for Human-interpretable Representation Learning
Entropy (Entropy), 2023
Emanuele Marconato
Baptiste Caramiaux
Stefano Teso
275
21
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14 Sep 2023
Learning multi-modal generative models with permutation-invariant encoders and tighter variational bounds
Marcel Hirt
Domenico Campolo
Victoria Leong
Juan-Pablo Ortega
DRL
359
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01 Sep 2023
Inducing Causal Structure for Abstractive Text Summarization
International Conference on Information and Knowledge Management (CIKM), 2023
Luyao Chen
Ruqing Zhang
Wei Huang
Wei Chen
Jiafeng Guo
Xueqi Cheng
CML
218
3
0
24 Aug 2023
Stable and Causal Inference for Discriminative Self-supervised Deep Visual Representations
IEEE International Conference on Computer Vision (ICCV), 2023
Yuewei Yang
Hai Helen Li
Yiran Chen
CML
OOD
254
2
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16 Aug 2023
Deep Generative Imputation Model for Missing Not At Random Data
International Conference on Information and Knowledge Management (CIKM), 2023
Jia-Lve Chen
Yuanbo Xu
Pengyang Wang
Yongjian Yang
SyDa
132
12
0
16 Aug 2023
Neural Latent Aligner: Cross-trial Alignment for Learning Representations of Complex, Naturalistic Neural Data
International Conference on Machine Learning (ICML), 2023
Cheol Jun Cho
Edward F. Chang
Gopala K. Anumanchipalli
218
9
0
12 Aug 2023
Identifiability Guarantees for Causal Disentanglement from Soft Interventions
Neural Information Processing Systems (NeurIPS), 2023
Jiaqi Zhang
C. Squires
Kristjan Greenewald
Akash Srivastava
Karthikeyan Shanmugam
Caroline Uhler
CML
361
87
0
12 Jul 2023
SepVAE: a contrastive VAE to separate pathological patterns from healthy ones
International Conference on Medical Imaging with Deep Learning (MIDL), 2023
Robin Louiset
Edouard Duchesnay
Antoine Grigis
Benoit Dufumier
Pietro Gori
DRL
242
7
0
12 Jul 2023
A Causal Ordering Prior for Unsupervised Representation Learning
Avinash Kori
Pedro Sanchez
Konstantinos Vilouras
Ben Glocker
Sotirios A. Tsaftaris
BDL
SSL
CML
312
2
0
11 Jul 2023
Additive Decoders for Latent Variables Identification and Cartesian-Product Extrapolation
Neural Information Processing Systems (NeurIPS), 2023
Sébastien Lachapelle
Divyat Mahajan
Ioannis Mitliagkas
Damien Scieur
290
44
0
05 Jul 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity
H. Aliee
Ferdinand Kapl
Soroor Hediyeh-zadeh
Fabian J. Theis
CML
286
9
0
02 Jul 2023
On the Identifiability of Quantized Factors
CLEaR (CLEaR), 2023
Vitória Barin Pacela
Kartik Ahuja
Damien Scieur
Pascal Vincent
OOD
CML
310
3
0
28 Jun 2023
High Fidelity Image Counterfactuals with Probabilistic Causal Models
International Conference on Machine Learning (ICML), 2023
Fabio De Sousa Ribeiro
Tian Xia
M. Monteiro
Nick Pawlowski
Ben Glocker
DiffM
230
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27 Jun 2023
Leveraging Task Structures for Improved Identifiability in Neural Network Representations
Jiajun He
Julien Horwood
Juyeon Heo
José Miguel Hernández-Lobato
CML
284
1
0
26 Jun 2023
Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models
International Conference on Learning Representations (ICLR), 2023
Zeyu Zhou
Ruqi Bai
Sean Kulinski
Murat Kocaoglu
David I. Inouye
CML
285
2
0
20 Jun 2023
Beyond Normal: On the Evaluation of Mutual Information Estimators
Neural Information Processing Systems (NeurIPS), 2023
Paweł Czyż
Frederic Grabowski
Julia E. Vogt
N. Beerenwinkel
Alexander Marx
252
53
0
19 Jun 2023
Identifiable causal inference with noisy treatment and no side information
Antti Pöllänen
Pekka Marttinen
CML
136
2
0
18 Jun 2023
BISCUIT: Causal Representation Learning from Binary Interactions
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Phillip Lippe
Sara Magliacane
Sindy Löwe
Yuki M. Asano
Taco S. Cohen
E. Gavves
CML
249
34
0
16 Jun 2023
Causal Mediation Analysis with Multi-dimensional and Indirectly Observed Mediators
Ziyang Jiang
Yi-Ling Liu
M. H. Klein
Ahmed Aloui
Yiman Ren
Keyu Li
Vahid Tarokh
David Carlson
CML
111
2
0
13 Jun 2023
Identification of Nonlinear Latent Hierarchical Models
Neural Information Processing Systems (NeurIPS), 2023
Lingjing Kong
Erdun Gao
Feng Xie
Eric Xing
Yuejie Chi
Kun Zhang
CML
247
25
0
13 Jun 2023
Partial Identifiability for Domain Adaptation
Lingjing Kong
Shaoan Xie
Weiran Yao
Yujia Zheng
Guan-Hong Chen
P. Stojanov
Victor Akinwande
Kun Zhang
273
14
0
10 Jun 2023
Understanding Masked Autoencoders via Hierarchical Latent Variable Models
Computer Vision and Pattern Recognition (CVPR), 2023
Lingjing Kong
Martin Q. Ma
Guan-Hong Chen
Eric Xing
Yuejie Chi
Louis-Philippe Morency
Kun Zhang
236
43
0
08 Jun 2023
Learning nonparametric latent causal graphs with unknown interventions
Neural Information Processing Systems (NeurIPS), 2023
Yibo Jiang
Bryon Aragam
CML
302
29
0
05 Jun 2023
Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
Neural Information Processing Systems (NeurIPS), 2023
Simon Buchholz
Goutham Rajendran
Elan Rosenfeld
Bryon Aragam
Bernhard Schölkopf
Pradeep Ravikumar
CML
370
77
0
04 Jun 2023
Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
Neural Information Processing Systems (NeurIPS), 2023
Valentyn Melnychuk
Dennis Frauen
Stefan Feuerriegel
528
13
0
02 Jun 2023
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