Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness

31 October 2018

Stefan Bauer

Papers citing "Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness"

47 / 47 papers shown

Title
Parameter Estimation using Reinforcement Learning Causal Curiosity: Limits and Challenges Miguel Arana-Catania Weisi Guo CML 30 0 0 13 May 2025
If Concept Bottlenecks are the Question, are Foundation Models the Answer? Nicola Debole Pietro Barbiero Francesco Giannini Andrea Passerini Stefano Teso Emanuele Marconato 158 0 0 28 Apr 2025
Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models X. Wang Haoyang Li Zeyang Zhang Hongyu Chen Wenwu Zhu LRM 84 0 0 28 Apr 2025
Towards Robust and Reliable Concept Representations: Reliability-Enhanced Concept Embedding Model Yuxuan Cai Xinbing Wang Satoshi Tsutsui Winnie Pang Bihan Wen 65 0 0 03 Feb 2025
Learning Invariant Causal Mechanism from Vision-Language Models Changwen Zheng Siyu Zhao Xingyu Zhang Jiangmeng Li Changwen Zheng Jingyao Wang CML BDL VLM 45 0 0 24 May 2024
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models Preben Ness D. Marijan Sunanda Bose CML 29 0 0 21 Aug 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 23 6 0 02 Jul 2023
On Counterfactual Data Augmentation Under Confounding Abbavaram Gowtham Reddy Saketh Bachu Saloni Dash Charchit Sharma Amit Sharma V. Balasubramanian CML BDL 33 0 0 29 May 2023
Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment Peng Jin Hao Li Ze-Long Cheng Jinfa Huang Zhennan Wang Li-ming Yuan Chang-rui Liu Jie Chen 38 32 0 20 May 2023
A Category-theoretical Meta-analysis of Definitions of Disentanglement Yivan Zhang Masashi Sugiyama 38 3 0 11 May 2023
Correcting Flaws in Common Disentanglement Metrics Louis Mahon Lei Shah Thomas Lukasiewicz CoGe DRL 37 3 0 05 Apr 2023
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting Shayan Shirahmad Gale Bagi Zahra Gharaee Oliver Schulte Mark Crowley OODD OOD 26 12 0 17 Feb 2023
Disentangled Representation Learning Xin Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 35 78 0 21 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 36 11 0 07 Nov 2022
DOT-VAE: Disentangling One Factor at a Time Vaishnavi Patil Matthew Evanusa J. JáJá CoGe DRL CML 23 1 0 19 Oct 2022
SW-VAE: Weakly Supervised Learn Disentangled Representation Via Latent Factor Swapping Jiageng Zhu Hanchen Xie Wael AbdAlmageed SSL CoGe DRL 35 4 0 21 Sep 2022
Weakly Supervised Invariant Representation Learning Via Disentangling Known and Unknown Nuisance Factors Jiageng Zhu Hanchen Xie Wael AbdAlmageed 32 1 0 15 Sep 2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift Yivan Zhang Jindong Wang Xingxu Xie Masashi Sugiyama OOD 42 1 0 03 Aug 2022
GlanceNets: Interpretabile, Leak-proof Concept-based Models Emanuele Marconato Andrea Passerini Stefano Teso 106 64 0 31 May 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 30 45 0 01 Apr 2022
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xia Hu Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 17 14 0 21 Jan 2022
Disentanglement and Generalization Under Correlation Shifts Christina M. Funke Paul Vicol Kuan-Chieh Jackson Wang Matthias Kümmerer R. Zemel Matthias Bethge OOD 39 7 0 29 Dec 2021
Latte: Cross-framework Python Package for Evaluation of Latent-Based Generative Models Alon Jacovi Junyoung Lee Alexander Lerch DRL 18 1 0 20 Dec 2021
On Causally Disentangled Representations Abbavaram Gowtham Reddy Benin Godfrey L V. Balasubramanian OOD CML 34 21 0 10 Dec 2021
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective Yuejiang Liu Riccardo Cadei Jonas Schweizer Sherwin Bahmani Alexandre Alahi OOD TTA 38 51 0 29 Nov 2021
Matching Learned Causal Effects of Neural Networks with Domain Priors Sai Srinivas Kancheti Abbavaram Gowtham Reddy V. Balasubramanian Amit Sharma CML 36 12 0 24 Nov 2021
Self-Supervised Learning Disentangled Group Representation as Feature Tan Wang Zhongqi Yue Jianqiang Huang Qianru Sun Hanwang Zhang OOD 36 67 0 28 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
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 32 80 0 08 Sep 2021
What can the millions of random treatments in nonexperimental data reveal about causes? Andre F. Ribeiro Frank Neffke Ricardo Hausmann CML 28 1 0 03 May 2021
Causal Attention for Vision-Language Tasks Xu Yang Hanwang Zhang Guojun Qi Jianfei Cai CML 28 148 0 05 Mar 2021
Counterfactual Zero-Shot and Open-Set Visual Recognition Zhongqi Yue Tan Wang Hanwang Zhang Qianru Sun Xiansheng Hua BDL 158 193 0 01 Mar 2021
Towards Building A Group-based Unsupervised Representation Disentanglement Framework Tao Yang Xuanchi Ren Yuwang Wang W. Zeng Nanning Zheng CoGe DRL 19 27 0 20 Feb 2021
Counterfactual Generative Networks Axel Sauer Andreas Geiger OOD BDL CML 41 123 0 15 Jan 2021
Measuring Disentanglement: A Review of Metrics M. Carbonneau Julian Zaïdi Jonathan Boilard G. Gagnon CoGe DRL 28 81 0 16 Dec 2020
Latent Causal Invariant Model Xinwei Sun Botong Wu Xiangyu Zheng Chang-Shu Liu Wei Chen Tao Qin Tie-Yan Liu OOD CML BDL 29 14 0 04 Nov 2020
On the Transfer of Disentangled Representations in Realistic Settings Andrea Dittadi Frederik Trauble Francesco Locatello M. Wuthrich Vaibhav Agrawal Ole Winther Stefan Bauer Bernhard Schölkopf OOD 35 39 0 27 Oct 2020
Interventional Few-Shot Learning Zhongqi Yue Hanwang Zhang Qianru Sun Xiansheng Hua 26 225 0 28 Sep 2020
Causal Intervention for Weakly-Supervised Semantic Segmentation Dong Zhang Hanwang Zhang Jinhui Tang Xiansheng Hua Qianru Sun CML ISeg 39 444 0 26 Sep 2020
Learning Disentangled Representations with Latent Variation Predictability Xinqi Zhu Chang Xu Dacheng Tao CoGe DRL 22 26 0 25 Jul 2020
A causal view of compositional zero-shot recognition Y. Atzmon Felix Kreuk Uri Shalit Gal Chechik OCL BDL CML 61 117 0 25 Jun 2020
Generative causal explanations of black-box classifiers Matthew R. O’Shaughnessy Gregory H. Canal Marissa Connor Mark A. Davenport Christopher Rozell CML 30 73 0 24 Jun 2020
Emergent Multi-Agent Communication in the Deep Learning Era Angeliki Lazaridou Marco Baroni AI4CE 48 197 0 03 Jun 2020
CausalVAE: Structured Causal Disentanglement in Variational Autoencoder Girish A. Koushik Furui Liu Zhitang Chen Xinwei Shen Jianye Hao Jun Wang OOD CoGe CML 41 44 0 18 Apr 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 26 21 0 26 Feb 2020
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 24 92 0 17 Nov 2019
Counterfactuals uncover the modular structure of deep generative models M. Besserve Arash Mehrjou Rémy Sun Bernhard Schölkopf DRL BDL DiffM 19 107 0 08 Dec 2018