Variational Autoencoders and Nonlinear ICA: A Unifying Framework

10 July 2019

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

50 / 132 papers shown

Title
Causality-Inspired Robustness for Nonlinear Models via Representation Learning Marin Šola Peter Bühlmann Xinwei Shen OOD 17 0 0 19 May 2025
Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning Xinyue Wang Zhen Zhang OffRL CML 37 0 0 13 May 2025
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 36 0 0 12 May 2025
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning Ruichu Cai Junjie Wan Weilin Chen Zeqin Yang Zijian Li Peng Zhen Jiecheng Guo CML 69 1 0 08 May 2025
Contextures: Representations from Contexts Runtian Zhai Kai Yang Che-Ping Tsai Burak Varici Zico Kolter Pradeep Ravikumar 226 0 0 02 May 2025
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 64 0 0 14 Apr 2025
Robustness of Nonlinear Representation Learning Simon Buchholz Bernhard Schölkopf OOD 248 3 0 19 Mar 2025
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 256 0 0 12 Mar 2025
Sanity Checking Causal Representation Learning on a Simple Real-World System Juan L. Gamella Simon Bing Jakob Runge CML 62 0 0 27 Feb 2025
Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens Samuele Bortolotti Emanuele Marconato Paolo Morettin Andrea Passerini Stefano Teso 66 2 0 16 Feb 2025
Sample-efficient Learning of Concepts with Theoretical Guarantees: from Data to Concepts without Interventions H. Fokkema T. Erven Sara Magliacane 75 1 0 10 Feb 2025
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 CoGe DRL 80 0 0 04 Feb 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 69 0 0 03 Jan 2025
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 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
Your Image is Secretly the Last Frame of a Pseudo Video Wenlong Chen Wenlin Chen Lapo Rastrelli Yingzhen Li DiffM VGen 39 0 0 26 Oct 2024
Counterfactual Generative Modeling with Variational Causal Inference Yulun Wu Louie McConnell Claudia Iriondo CML BDL 27 0 0 16 Oct 2024
Rethinking Fair Representation Learning for Performance-Sensitive Tasks Charles Jones Fabio De Sousa Ribeiro Mélanie Roschewitz Daniel Coelho De Castro Ben Glocker FaML OOD CML 148 1 0 05 Oct 2024
Mitigating Propensity Bias of Large Language Models for Recommender Systems Guixian Zhang Guan Yuan Debo Cheng Lin Liu Jiuyong Li Shichao Zhang 47 2 0 30 Sep 2024
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 23 2 0 09 Sep 2024
Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations Yupei Yang Erdun Gao Fan Feng Xinyue Wang Shikui Tu Lei Xu CML OOD TTA 45 1 0 30 Jul 2024
Linear causal disentanglement via higher-order cumulants Paula Leyes Carreno Chiara Meroni A. Seigal CML 38 0 0 05 Jul 2024
Learning Discrete Concepts in Latent Hierarchical Models Lingjing Kong Guan-Hong Chen Erdun Gao Eric P. Xing Yuejie Chi Kun Zhang 56 4 0 01 Jun 2024
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
Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models Aneesh Komanduri Chengli Zhao Feng Chen Xintao Wu CML DiffM 42 5 0 27 Apr 2024
CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation Baoyu Jing Dawei Zhou Kan Ren Carl Yang CML AI4TS 37 7 0 18 Mar 2024
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders Yaniv Yacoby Weiwei Pan Finale Doshi-Velez DRL 34 0 0 13 Mar 2024
Algorithmic Identification of Essential Exogenous Nodes for Causal Sufficiency in Brain Networks Abdolmahdi Bagheri Mahdi Dehshiri Babak N. Araabi Alireza Akhondi-Asl CML 39 2 0 08 Mar 2024
Towards Controllable Time Series Generation Yifan Bao Yihao Ang Qiang Huang Anthony K. H. Tung Zhiyong Huang DiffM 51 4 0 06 Mar 2024
Separating common from salient patterns with Contrastive Representation Learning Robin Louiset Edouard Duchesnay Antoine Grigis Pietro Gori SSL DRL 51 1 0 19 Feb 2024
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
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation S. Chatterjee Franziska Gaidzik Alessandro Sciarra Hendrik Mattern G. Janiga Oliver Speck Andreas Nürnberger S. Pathiraja 52 0 0 25 Dec 2023
Predictive variational autoencoder for learning robust representations of time-series data Julia Huiming Wang Dexter Tsin Tatiana Engel CML OOD AI4TS 37 2 0 12 Dec 2023
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 Zijian Li Zunhong Xu Ruichu Cai Zhenhui Yang Yuguang Yan Zhifeng Hao Guan-Hong Chen Kun Zhang 27 9 0 08 Nov 2023
Towards a Unified Framework of Contrastive Learning for Disentangled Representations Stefan Matthes Zhiwei Han Hao Shen 42 4 0 08 Nov 2023
Causal Representation Learning Made Identifiable by Grouping of Observational Variables H. Morioka Aapo Hyvarinen OOD CML BDL 38 9 0 24 Oct 2023
High Dimensional Causal Inference with Variational Backdoor Adjustment Daniel Israel Aditya Grover Guy Van den Broeck CML 18 0 0 09 Oct 2023
USTEP: Spatio-Temporal Predictive Learning under A Unified View Cheng Tan Jue Wang Zhangyang Gao Siyuan Li Stan Z. Li 40 1 0 09 Oct 2023
Subspace Identification for Multi-Source Domain Adaptation Zijian Li Ruichu Cai Guan-Hong Chen Boyang Sun Zhifeng Hao Kun Zhang 41 33 0 07 Oct 2023
Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank Mouxiang Chen Chenghao Liu Zemin Liu Zhuo Li Jianling Sun CML 34 2 0 27 Sep 2023
Word Embedding with Neural Probabilistic Prior Shaogang Ren Dingcheng Li P. Li BDL 27 0 0 21 Sep 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 36 6 0 02 Jul 2023
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 Zeyu Zhou Ruqi Bai Sean Kulinski Murat Kocaoglu David I. Inouye CML 26 1 0 20 Jun 2023
Partial Identifiability for Domain Adaptation Lingjing Kong Shaoan Xie Weiran Yao Yujia Zheng Guan-Hong Chen P. Stojanov Victor Akinwande Kun Zhang 58 9 0 10 Jun 2023
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 32 57 0 01 Jun 2023
Neuro-Causal Factor Analysis Alex Markham Ming Liu Bryon Aragam Liam Solus CML 35 3 0 31 May 2023
Discovering Predictable Latent Factors for Time Series Forecasting Jingyi Hou Zhen Dong Jiayu Zhou Zhijie Liu AI4TS BDL 40 1 0 18 Mar 2023
Measuring axiomatic soundness of counterfactual image models M. Monteiro Fabio De Sousa Ribeiro Nick Pawlowski Daniel Coelho De Castro Ben Glocker 49 25 0 02 Mar 2023