Invariant Risk Minimization

5 July 2019

Papers citing "Invariant Risk Minimization"

50 / 1,404 papers shown

Title
Invariant Policy Optimization: Towards Stronger Generalization in Reinforcement Learning Anoopkumar Sonar Vincent Pacelli Anirudha Majumdar 10 53 0 01 Jun 2020
Towards intervention-centric causal reasoning in learning agents B. Lansdell LRM CML 11 0 0 26 May 2020
An Analysis of the Adaptation Speed of Causal Models Rémi Le Priol Reza Babanezhad Harikandeh Yoshua Bengio Simon Lacoste-Julien CML 19 14 0 18 May 2020
Adaptive Invariance for Molecule Property Prediction Wengong Jin Regina Barzilay Tommi Jaakkola 6 7 0 05 May 2020
Selecting Data Augmentation for Simulating Interventions Maximilian Ilse Jakub M. Tomczak Patrick Forré OOD CML 21 18 0 04 May 2020
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems Sergey Levine Aviral Kumar George Tucker Justin Fu OffRL GP 340 1,960 0 04 May 2020
A Causal View on Robustness of Neural Networks Cheng Zhang Kun Zhang Yingzhen Li CML OOD 21 85 0 03 May 2020
Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation Xi Wu Yang Guo Jiefeng Chen Yingyu Liang S. Jha P. Chalasani OOD UQCV 11 6 0 22 Apr 2020
Causality-aware counterfactual confounding adjustment for feature representations learned by deep models E. C. Neto AI4CE OOD BDL CML 22 2 0 20 Apr 2020
Learning What Makes a Difference from Counterfactual Examples and Gradient Supervision Damien Teney Ehsan Abbasnejad Anton Van Den Hengel OOD SSL CML 26 118 0 20 Apr 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 55 1,985 0 16 Apr 2020
Continual Reinforcement Learning with Multi-Timescale Replay Christos Kaplanis Claudia Clopath Murray Shanahan CLL 14 14 0 16 Apr 2020
WQT and DG-YOLO: towards domain generalization in underwater object detection Hong Liu Pinhao Song Runwei Ding 9 26 0 14 Apr 2020
An Empirical Study of Invariant Risk Minimization Yo Joong Choe Jiyeon Ham Kyubyong Park OOD 20 50 0 10 Apr 2020
Improving out-of-distribution generalization via multi-task self-supervised pretraining Isabela Albuquerque Nikhil Naik Junnan Li N. Keskar R. Socher SSL OOD 30 40 0 30 Mar 2020
Efficient Domain Generalization via Common-Specific Low-Rank Decomposition Vihari Piratla Praneeth Netrapalli Sunita Sarawagi OOD 14 216 0 28 Mar 2020
Log-Likelihood Ratio Minimizing Flows: Towards Robust and Quantifiable Neural Distribution Alignment Ben Usman Avneesh Sud Nick Dufour Kate Saenko OOD 9 13 0 26 Mar 2020
Invariant Rationalization Shiyu Chang Yang Zhang Mo Yu Tommi Jaakkola 179 201 0 22 Mar 2020
Overinterpretation reveals image classification model pathologies Brandon Carter Siddhartha Jain Jonas W. Mueller David K Gifford FAtt 30 50 0 19 Mar 2020
Invariant Causal Prediction for Block MDPs Amy Zhang Clare Lyle Shagun Sodhani Angelos Filos Marta Z. Kwiatkowska Joelle Pineau Y. Gal Doina Precup OffRL AI4CE OOD 29 139 0 12 Mar 2020
Domain Adaptation with Conditional Distribution Matching and Generalized Label Shift Rémi Tachet des Combes Han Zhao Yu-Xiang Wang Geoffrey J. Gordon OOD AAML VLM 31 183 0 10 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 2020
Unshuffling Data for Improved Generalization Damien Teney Ehsan Abbasnejad Anton Van Den Hengel OOD 23 76 0 27 Feb 2020
I-SPEC: An End-to-End Framework for Learning Transportable, Shift-Stable Models Adarsh Subbaswamy S. Saria OOD 33 14 0 20 Feb 2020
Partial Optimal Transport with Applications on Positive-Unlabeled Learning Laetitia Chapel Mokhtar Z. Alaya Gilles Gasso OT 4 8 0 19 Feb 2020
Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example Serena Booth Yilun Zhou Ankit J. Shah J. Shah BDL 17 2 0 19 Feb 2020
Invariant Risk Minimization Games Kartik Ahuja Karthikeyan Shanmugam Kush R. Varshney Amit Dhurandhar OOD 24 244 0 11 Feb 2020
Adversarial Filters of Dataset Biases Ronan Le Bras Swabha Swayamdipta Chandra Bhagavatula Rowan Zellers Matthew E. Peters Ashish Sabharwal Yejin Choi 36 220 0 10 Feb 2020
Time Series Alignment with Global Invariances Titouan Vayer R. Tavenard Laetitia Chapel Nicolas Courty Rémi Flamary Yann Soullard AI4TS 20 16 0 10 Feb 2020
Few-shot Domain Adaptation by Causal Mechanism Transfer Takeshi Teshima Issei Sato Masashi Sugiyama OOD CML TTA 33 86 0 10 Feb 2020
Causality matters in medical imaging Daniel Coelho De Castro Ian Walker Ben Glocker CML 23 337 0 17 Dec 2019
Towards Causal VQA: Revealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing Vedika Agarwal Rakshith Shetty Mario Fritz CML AAML 32 155 0 16 Dec 2019
Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers Divyat Mahajan Chenhao Tan Amit Sharma OOD CML 22 206 0 06 Dec 2019
Achieving Robustness in the Wild via Adversarial Mixing with Disentangled Representations Sven Gowal Chongli Qin Po-Sen Huang taylan. cemgil Krishnamurthy Dvijotham Timothy A. Mann Pushmeet Kohli AAML OOD 16 57 0 06 Dec 2019
Observational Overfitting in Reinforcement Learning Xingyou Song Yiding Jiang Stephen Tu Yilun Du Behnam Neyshabur OffRL 33 138 0 06 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 14 1,194 0 20 Nov 2019
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
Increasing Robustness to Spurious Correlations using Forgettable Examples Yadollah Yaghoobzadeh Soroush Mehri Remi Tachet Timothy J. Hazen Alessandro Sordoni OOD 13 18 0 10 Nov 2019
Generalizing to unseen domains via distribution matching Isabela Albuquerque João Monteiro Mohammad Javad Darvishi Bayazi T. Falk Ioannis Mitliagkas OOD 24 154 0 03 Nov 2019
Causal bootstrapping Max A. Little Reham Badawy CML 10 20 0 21 Oct 2019
Robust Learning with the Hilbert-Schmidt Independence Criterion D. Greenfeld Uri Shalit OOD 22 55 0 01 Oct 2019
Predicting with High Correlation Features Devansh Arpit Caiming Xiong R. Socher OODD OOD 14 7 0 01 Oct 2019
Alleviating Privacy Attacks via Causal Learning Shruti Tople Amit Sharma A. Nori MIACV OOD 33 32 0 27 Sep 2019
Learning Invariants through Soft Unification Nuri Cingillioglu A. Russo NAI 13 2 0 16 Sep 2019
Modular Meta-Learning with Shrinkage Yutian Chen A. Friesen Feryal M. P. Behbahani Arnaud Doucet David Budden Matthew W. Hoffman Nando de Freitas KELM OffRL 20 35 0 12 Sep 2019
Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning Vishwali Mhasawade N. Rehman R. Chunara OOD 14 9 0 24 Aug 2019
Unsupervised Recalibration Albert Ziegler Paweł Czyż 19 1 0 24 Aug 2019
Info Intervention Heyang Gong Zhu Ke CML 16 0 0 24 Jul 2019
Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions Matthew Faw Rajat Sen Karthikeyan Shanmugam C. Caramanis Sanjay Shakkottai 33 3 0 23 Jul 2019
A Unifying Causal Framework for Analyzing Dataset Shift-stable Learning Algorithms Adarsh Subbaswamy Bryant Chen S. Saria OOD 19 18 0 27 May 2019