A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms

30 January 2019

Papers citing "A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms"

50 / 62 papers shown

Title
A Theoretical Analysis of Compositional Generalization in Neural Networks: A Necessary and Sufficient Condition Yuanpeng Li CoGe 109 0 0 05 May 2025
Transfer Learning in Latent Contextual Bandits with Covariate Shift Through Causal Transportability Mingwei Deng Ville Kyrki Dominik Baumann 36 0 0 27 Feb 2025
Rethinking Meta-Learning from a Learning Lens Jingyao Wang Wenwen Qiang Chuxiong Sun Lingyu Si Jiangmeng Li 41 1 0 13 Sep 2024
Breaking Neural Network Scaling Laws with Modularity Akhilan Boopathy Sunshine Jiang William Yue Jaedong Hwang Abhiram Iyer Ila Fiete OOD 34 2 0 09 Sep 2024
Memory Mosaics Jianyu Zhang Niklas Nolte Ranajoy Sadhukhan Beidi Chen Léon Bottou VLM 54 3 0 10 May 2024
CASPER: Causality-Aware Spatiotemporal Graph Neural Networks for Spatiotemporal Time Series Imputation Baoyu Jing Dawei Zhou Kan Ren Carl Yang CML AI4TS 32 6 0 18 Mar 2024
Towards Controllable Time Series Generation Yifan Bao Yihao Ang Qiang Huang Anthony K. H. Tung Zhiyong Huang DiffM 30 4 0 06 Mar 2024
InfFeed: Influence Functions as a Feedback to Improve the Performance of Subjective Tasks Somnath Banerjee Maulindu Sarkar Punyajoy Saha Binny Mathew Animesh Mukherjee TDI 21 0 0 22 Feb 2024
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization Tianrui Jia Haoyang Li Cheng Yang Tao Tao Chuan Shi OOD 20 17 0 18 Dec 2023
Continual Invariant Risk Minimization Francesco Alesiani Shujian Yu Mathias Niepert OOD 18 1 0 21 Oct 2023
Neural Relational Inference with Fast Modular Meta-learning Ferran Alet Erica Weng Tomás Lozano Pérez L. Kaelbling 47 55 0 10 Oct 2023
CausalOps -- Towards an Industrial Lifecycle for Causal Probabilistic Graphical Models R. Maier A. Schlattl Thomas Guess J. Mottok AI4CE 26 1 0 02 Aug 2023
Conditionally Invariant Representation Learning for Disentangling Cellular Heterogeneity H. Aliee Ferdinand Kapl Soroor Hediyeh-zadeh Fabian J. Theis CML 20 6 0 02 Jul 2023
Reusable Slotwise Mechanisms Trang Nguyen Amin Mansouri Kanika Madan Khuong N. Nguyen Kartik Ahuja Dianbo Liu Yoshua Bengio OCL 22 4 0 21 Feb 2023
Deep Causal Learning for Robotic Intelligence Y. Li CML 19 5 0 23 Dec 2022
$Trust Your $\nabla$: Gradient-based Intervention Targeting for Causal Discovery$ Trust Your $\nabla$ : Gradient-based Intervention Targeting for Causal Discovery Mateusz Olko Michal Zajac A. Nowak Nino Scherrer Yashas Annadani Stefan Bauer Lukasz Kucinski Piotr Milos CML 24 2 0 24 Nov 2022
A Short Survey of Systematic Generalization Yuanpeng Li AI4CE 22 1 0 22 Nov 2022
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 22 77 0 21 Nov 2022
Deep Causal Learning: Representation, Discovery and Inference Zizhen Deng Xiaolong Zheng Hu Tian D. Zeng CML BDL 26 11 0 07 Nov 2022
Neural Attentive Circuits Nasim Rahaman M. Weiß Francesco Locatello C. Pal Yoshua Bengio Bernhard Schölkopf Erran L. Li Nicolas Ballas 19 6 0 14 Oct 2022
On a Built-in Conflict between Deep Learning and Systematic Generalization Yuanpeng Li OOD 21 0 0 24 Aug 2022
Meta-Causal Feature Learning for Out-of-Distribution Generalization Yuqing Wang Xiangxian Li Zhuang Qi Jingyu Li Xuelong Li Xiangxu Meng Lei Meng OOD OODD BDL 25 25 0 22 Aug 2022
Towards Intercultural Affect Recognition: Audio-Visual Affect Recognition in the Wild Across Six Cultures Leena Mathur R. Adolphs Maja J. Matarić CVBM 17 1 0 31 Jul 2022
Equivariant Representation Learning via Class-Pose Decomposition G. Marchetti Gustaf Tegnér Anastasiia Varava Danica Kragic DRL 22 14 0 07 Jul 2022
Towards Understanding How Machines Can Learn Causal Overhypotheses Eliza Kosoy David M. Chan Adrian Liu Jasmine Collins Bryanna Kaufmann Sandy Han Huang Jessica B. Hamrick John F. Canny Nan Rosemary Ke Alison Gopnik CML AI4CE 21 18 0 16 Jun 2022
On the Generalization and Adaption Performance of Causal Models Nino Scherrer Anirudh Goyal Stefan Bauer Yoshua Bengio Nan Rosemary Ke CML OOD BDL TTA 23 8 0 09 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry Julius von Kügelgen Bernhard Schölkopf 30 48 0 04 Jun 2022
Do learned representations respect causal relationships? Lan Wang Vishnu Naresh Boddeti NAI CML OOD 18 6 0 02 Apr 2022
Interventions, Where and How? Experimental Design for Causal Models at Scale P. Tigas Yashas Annadani Andrew Jesson Bernhard Schölkopf Y. Gal Stefan Bauer CML 31 48 0 03 Mar 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 16 4 0 04 Feb 2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias Shaohua Fan Xiao Wang Chuan Shi Kun Kuang Nian Liu Bai Wang AI4CE 29 38 0 19 Jan 2022
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 37 81 0 20 Nov 2021
Dynamic Inference with Neural Interpreters Nasim Rahaman Muhammad Waleed Gondal S. Joshi Peter V. Gehler Yoshua Bengio Francesco Locatello Bernhard Schölkopf 21 31 0 12 Oct 2021
Learning Neural Causal Models with Active Interventions Nino Scherrer O. Bilaniuk Yashas Annadani Anirudh Goyal Patrick Schwab Bernhard Schölkopf Michael C. Mozer Yoshua Bengio Stefan Bauer Nan Rosemary Ke CML 33 42 0 06 Sep 2021
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning Nan Rosemary Ke Aniket Didolkar Sarthak Mittal Anirudh Goyal Guillaume Lajoie Stefan Bauer Danilo Jimenez Rezende Yoshua Bengio Michael C. Mozer C. Pal CML 19 54 0 02 Jul 2021
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures Yashas Annadani Jonas Rothfuss Alexandre Lacoste Nino Scherrer Anirudh Goyal Yoshua Bengio Stefan Bauer BDL CML 13 48 0 14 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? Dinghuai Zhang Kartik Ahuja Yilun Xu Yisen Wang Aaron Courville OOD 18 95 0 05 Jun 2021
A Bit More Bayesian: Domain-Invariant Learning with Uncertainty Zehao Xiao Jiayi Shen Xiantong Zhen Ling Shao Cees G. M. Snoek BDL UQCV OOD 16 39 0 09 May 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 37 68 0 11 Apr 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 31 108 0 08 Mar 2021
Causal Attention for Vision-Language Tasks Xu Yang Hanwang Zhang Guojun Qi Jianfei Cai CML 23 148 0 05 Mar 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 32 296 0 03 Mar 2021
Domain Generalization: A Survey Kaiyang Zhou Ziwei Liu Yu Qiao Tao Xiang Chen Change Loy OOD AI4CE 32 980 0 03 Mar 2021
Counterfactual Generative Networks Axel Sauer Andreas Geiger OOD BDL CML 28 123 0 15 Jan 2021
Learning Causal Semantic Representation for Out-of-Distribution Prediction Chang-Shu Liu Xinwei Sun Jindong Wang Haoyue Tang Tao Li Tao Qin Wei Chen Tie-Yan Liu CML OODD OOD 19 104 0 03 Nov 2020
S2RMs: Spatially Structured Recurrent Modules Nasim Rahaman Anirudh Goyal Muhammad Waleed Gondal M. Wuthrich Stefan Bauer Yash Sharma Yoshua Bengio Bernhard Schölkopf 16 14 0 13 Jul 2020
A causal view of compositional zero-shot recognition Y. Atzmon Felix Kreuk Uri Shalit Gal Chechik OCL BDL CML 45 117 0 25 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 22 229 0 11 Jun 2020
NestedVAE: Isolating Common Factors via Weak Supervision M. Vowels Necati Cihan Camgöz Richard Bowden CML DRL 11 21 0 26 Feb 2020
The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence G. Marcus VLM 24 352 0 14 Feb 2020