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
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 53 41 0 06 Feb 2023
Unpaired Multi-Domain Causal Representation Learning Nils Sturma C. Squires Mathias Drton Caroline Uhler OOD CML 48 20 0 02 Feb 2023
A Survey of Methods, Challenges and Perspectives in Causality Gaël Gendron Michael Witbrock Gillian Dobbie OOD AI4CE CML 44 13 0 01 Feb 2023
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
eVAE: Evolutionary Variational Autoencoder Zhangkai Wu LongBing Cao Lei Qi BDL DRL 40 10 0 01 Jan 2023
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects Thanh Vinh Vo Arnab Bhattacharyya Young Lee Tze-Yun Leong FedML 33 19 0 01 Jan 2023
ContraFeat: Contrasting Deep Features for Semantic Discovery Xinqi Zhu Chang Xu Dacheng Tao DRL 31 2 0 14 Dec 2022
Linear Causal Disentanglement via Interventions C. Squires A. Seigal Salil Bhate Caroline Uhler CML 29 66 0 29 Nov 2022
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 39 78 0 21 Nov 2022
Representational dissimilarity metric spaces for stochastic neural networks Lyndon Duong Jingyang Zhou Josue Nassar Jules Berman Jeroen Olieslagers Alex H. Williams 30 19 0 21 Nov 2022
Confounder Balancing for Instrumental Variable Regression with Latent Variable Anpeng Wu Kun Kuang Ruoxuan Xiong Bo Li Fei Wu CML 47 0 0 18 Nov 2022
Mechanistic Mode Connectivity Ekdeep Singh Lubana Eric J. Bigelow Robert P. Dick David M. Krueger Hidenori Tanaka 34 45 0 15 Nov 2022
Disentangling Variational Autoencoders Rafael Pastrana CoGe DRL 38 4 0 14 Nov 2022
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling Romain Lopez Natavsa Tagasovska Stephen Ra K. Cho J. Pritchard Aviv Regev OOD CML DRL 36 35 0 07 Nov 2022
Temporally Disentangled Representation Learning Weiran Yao Guangyi Chen Kun Zhang CML BDL OOD 34 49 0 24 Oct 2022
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 Qi Lyu Xiao Fu CoGe 31 0 0 14 Oct 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 41 33 0 13 Oct 2022
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions V. T. Trifunov M. Shadaydeh Joachim Denzler CML BDL 34 3 0 23 Sep 2022
Fair Inference for Discrete Latent Variable Models Rashidul Islam Shimei Pan James R. Foulds FaML 53 1 0 15 Sep 2022
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning Ruichu Cai Weilin Chen Zeqin Yang Shu Wan Chen Zheng Xiaoqing Yang Jiecheng Guo CML BDL 40 12 0 09 Aug 2022
Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning Damien Teney Maxime Peyrard Ehsan Abbasnejad 43 28 0 06 Jul 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 57 10 0 28 Jun 2022
Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning Cheng Tan Zhangyang Gao Lirong Wu Yongjie Xu Jun Xia Siyuan Li Stan Z. Li 51 107 0 24 Jun 2022
Identifiability of deep generative models without auxiliary information Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 31 49 0 20 Jun 2022
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 Patrik Reizinger Luigi Gresele Jack Brady Julius von Kügelgen Dominik Zietlow Bernhard Schölkopf Georg Martius Wieland Brendel M. Besserve DRL 40 19 0 06 Jun 2022
Weakly Supervised Representation Learning with Sparse Perturbations Kartik Ahuja Jason S. Hartford Yoshua Bengio SSL 35 58 0 02 Jun 2022
Top-down inference in an early visual cortex inspired hierarchical Variational Autoencoder F. Csikor B. Meszéna Bence Szabó Gergő Orbán BDL DRL 34 5 0 01 Jun 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 111 64 0 31 May 2022
Unsupervised Mismatch Localization in Cross-Modal Sequential Data with Application to Mispronunciations Localization Wei Wei Hengguan Huang Xiangming Gu Hao Wang Ye Wang BDL 32 0 0 05 May 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 28 48 0 01 May 2022
Weakly supervised causal representation learning Johann Brehmer P. D. Haan Phillip Lippe Taco S. Cohen OOD CML 41 122 0 30 Mar 2022
Multi-Instance Causal Representation Learning for Instance Label Prediction and Out-of-Distribution Generalization Weijia Zhang Xuanhui Zhang Hanwen Deng Min-Ling Zhang 27 22 0 25 Feb 2022
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 22 0 0 14 Feb 2022
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
Right for the Right Latent Factors: Debiasing Generative Models via Disentanglement Xiaoting Shao Karl Stelzner Kristian Kersting CML DRL 34 3 0 01 Feb 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 39 7 0 29 Dec 2021
MoRe-Fi: Motion-robust and Fine-grained Respiration Monitoring via Deep-Learning UWB Radar Tianyue Zheng Zhe Chen Shujie Zhang Chao Cai Jun Luo 29 95 0 16 Nov 2021
Unsupervised Learning of Compositional Energy Concepts Yilun Du Shuang Li Yash Sharma J. Tenenbaum Igor Mordatch CoGe OCL 32 76 0 04 Nov 2021
Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning Kartik Ahuja Jason S. Hartford Yoshua Bengio 34 38 0 29 Oct 2021
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 36 34 0 27 Oct 2021
Contrastively Disentangled Sequential Variational Autoencoder M. Kiener Weiran Wang Michael Gerndt CoGe DRL 39 40 0 22 Oct 2021
Identifiable Deep Generative Models via Sparse Decoding Gemma E. Moran Dhanya Sridhar Yixin Wang David M. Blei BDL 31 45 0 20 Oct 2021
Discovery of Single Independent Latent Variable Uri Shaham Jonathan Svirsky Ori Katz Ronen Talmon CML 30 2 0 12 Oct 2021
Learning Temporally Causal Latent Processes from General Temporal Data Weiran Yao Yuewen Sun Alex Ho Changyin Sun Kun Zhang BDL CML 37 85 0 11 Oct 2021
$β$ -Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap Pengzhou (Abel) Wu Kenji Fukumizu CML 35 14 0 11 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 30 3 0 30 Sep 2021
Be More Active! Understanding the Differences between Mean and Sampled Representations of Variational Autoencoders Lisa Bonheme M. Grzes DRL 21 6 0 26 Sep 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 37 82 0 08 Sep 2021