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Causal inference using invariant prediction: identification and confidence intervals

6 January 2015

Papers citing "Causal inference using invariant prediction: identification and confidence intervals"

50 / 493 papers shown

Title
Sample-Efficient Reinforcement Learning in the Presence of Exogenous Information Yonathan Efroni Dylan J. Foster Dipendra Kumar Misra A. Krishnamurthy John Langford OffRL 77 25 0 09 Jun 2022
Enhancing Distributional Stability among Sub-populations Jiashuo Liu Jiayun Wu Jie Peng Xiaoyu Wu Zheyan Shen Yangqiu Song Peng Cui OOD 44 3 0 07 Jun 2022
Active Bayesian Causal Inference Christian Toth Lars Lorch Christian Knoll Andreas Krause Franz Pernkopf Robert Peharz Julius von Kügelgen 83 27 0 04 Jun 2022
Causal Discovery in Heterogeneous Environments Under the Sparse Mechanism Shift Hypothesis Ronan Perry Julius von Kügelgen Bernhard Schölkopf 98 50 0 04 Jun 2022
BaCaDI: Bayesian Causal Discovery with Unknown Interventions Alexander Hagele Jonas Rothfuss Lars Lorch Vignesh Ram Somnath Bernhard Schölkopf Andreas Krause CML BDL 110 22 0 03 Jun 2022
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions Amrith Rajagopal Setlur Benjamin Eysenbach Virginia Smith Sergey Levine 73 18 0 03 Jun 2022
In the Eye of the Beholder: Robust Prediction with Causal User Modeling Amir Feder G. Horowitz Yoav Wald Roi Reichart Nir Rosenfeld OOD 75 7 0 01 Jun 2022
Differentiable Invariant Causal Discovery Yu Wang An Zhang Xiang Wang Yancheng Yuan Xiangnan He Tat-Seng Chua OOD CML 120 1 0 31 May 2022
PAC Generalization via Invariant Representations Advait Parulekar Karthikeyan Shanmugam Sanjay Shakkottai 78 4 0 30 May 2022
The Missing Invariance Principle Found -- the Reciprocal Twin of Invariant Risk Minimization Dongsung Huh A. Baidya OOD 58 8 0 29 May 2022
Detecting hidden confounding in observational data using multiple environments R. Karlsson Jesse H. Krijthe CML OOD 82 13 0 27 May 2022
An Empirical Study on Distribution Shift Robustness From the Perspective of Pre-Training and Data Augmentation Ziquan Liu Yi Tian Xu Yuanhong Xu Qi Qian Hao Li Rong Jin Xiangyang Ji Antoni B. Chan OOD 87 16 0 25 May 2022
Causal Machine Learning for Healthcare and Precision Medicine Pedro Sanchez J. Voisey Tian Xia Hannah I. Watson Alison Q. OÑeil Sotirios A. Tsaftaris OOD CML 96 123 0 23 May 2022
Improving Multi-Task Generalization via Regularizing Spurious Correlation Ziniu Hu Zhe Zhao Xinyang Yi Tiansheng Yao Lichan Hong Yizhou Sun Ed H. Chi OOD LRM 142 30 0 19 May 2022
Diverse Weight Averaging for Out-of-Distribution Generalization Alexandre Ramé Matthieu Kirchmeyer Thibaud Rahier A. Rakotomamonjy Patrick Gallinari Matthieu Cord OOD 256 138 0 19 May 2022
An Invariant Matching Property for Distribution Generalization under Intervened Response Kang Du Yu Xiang OOD 69 4 0 18 May 2022
Searching for subgroup-specific associations while controlling the false discovery rate M. Sesia Tianshu Sun 78 0 0 17 May 2022
Scalable Regularised Joint Mixture Models Thomas Lartigue S. Mukherjee 51 0 0 03 May 2022
From graphs to DAGs: a low-complexity model and a scalable algorithm Shuyu Dong Michèle Sebag CML 56 5 0 10 Apr 2022
Last Layer Re-Training is Sufficient for Robustness to Spurious Correlations Polina Kirichenko Pavel Izmailov A. Wilson OOD 97 339 0 06 Apr 2022
Do learned representations respect causal relationships? Lan Wang Vishnu Boddeti NAI CML OOD 82 6 0 02 Apr 2022
From Statistical to Causal Learning Bernhard Schölkopf Julius von Kügelgen CML 97 46 0 01 Apr 2022
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data Siyuan Guo V. Tóth Bernhard Schölkopf Ferenc Huszár CML 92 37 0 29 Mar 2022
Invariance Learning based on Label Hierarchy S. Toyota Kenji Fukumizu OOD 60 1 0 29 Mar 2022
Core Risk Minimization using Salient ImageNet Sahil Singla Mazda Moayeri Soheil Feizi 88 14 0 28 Mar 2022
Causality Inspired Representation Learning for Domain Generalization Fangrui Lv Jian Liang Shuang Li Bin Zang Chi Harold Liu Ziteng Wang Di Liu CML OOD 122 174 0 27 Mar 2022
Out-of-distribution Generalization with Causal Invariant Transformations Ruoyu Wang Mingyang Yi Zhitang Chen Shengyu Zhu OOD OODD 84 60 0 22 Mar 2022
WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Jean-Christophe Gagnon-Audet Kartik Ahuja Mohammad Javad Darvishi Bayazi Pooneh Mousavi G. Dumas Irina Rish OOD CML AI4TS 109 32 0 18 Mar 2022
Identifiability of Sparse Causal Effects using Instrumental Variables Niklas Pfister J. Peters CML 48 10 0 17 Mar 2022
ZIN: When and How to Learn Invariance Without Environment Partition? Yong Lin Shengyu Zhu Lu Tan Peng Cui OOD CML 88 69 0 11 Mar 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 141 50 0 03 Mar 2022
Local Constraint-Based Causal Discovery under Selection Bias Philip Versteeg Cheng Zhang Joris M. Mooij CML 47 13 0 03 Mar 2022
Towards IID representation learning and its application on biomedical data Jiqing Wu I. Zlobec Maxime W. Lafarge Yukun He V. Koelzer OOD CML 41 4 0 01 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 98 23 0 25 Feb 2022
Generalizable Information Theoretic Causal Representation Mengyue Yang Xin-Qiang Cai Furui Liu Xu Chen Zhitang Chen Jianye Hao Jun Wang OOD CML 120 1 0 17 Feb 2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization Elan Rosenfeld Pradeep Ravikumar Andrej Risteski OOD 83 82 0 14 Feb 2022
Evaluation Methods and Measures for Causal Learning Algorithms Lu Cheng Ruocheng Guo Raha Moraffah Paras Sheth K. S. Candan Huan Liu CML ELM 97 54 0 07 Feb 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 54 4 0 04 Feb 2022
Exploiting Independent Instruments: Identification and Distribution Generalization Sorawit Saengkyongam Leonard Henckel Niklas Pfister J. Peters 74 18 0 03 Feb 2022
Influence-Augmented Local Simulators: A Scalable Solution for Fast Deep RL in Large Networked Systems Miguel Suau Jinke He M. Spaan F. Oliehoek 58 4 0 03 Feb 2022
Invariant Ancestry Search Phillip B. Mogensen Nikolaj Thams J. Peters 87 5 0 02 Feb 2022
On the Limitations of General Purpose Domain Generalisation Methods Henry Gouk Ondrej Bohdal Da Li Timothy M. Hospedales 75 11 0 01 Feb 2022
Provable Domain Generalization via Invariant-Feature Subspace Recovery Haoxiang Wang Haozhe Si Yue Liu Han Zhao OOD 128 35 0 30 Jan 2022
Transferability in Deep Learning: A Survey Junguang Jiang Yang Shu Jianmin Wang Mingsheng Long OOD 88 104 0 15 Jan 2022
Automated causal inference in application to randomized controlled clinical trials Ji Q. Wu N. Horeweg M. de Bruyn R. Nout I. Jürgenliemk-Schulz ... H. Nijman V. Smit T. Bosse C. Creutzberg V. Koelzer CML 62 14 0 15 Jan 2022
Efficiently Disentangle Causal Representations Yuanpeng Li Joel Hestness Mohamed Elhoseiny Liang Zhao Kenneth Church OOD CML 29 1 0 06 Jan 2022
Balancing Fairness and Robustness via Partial Invariance Moulik Choraria Ibtihal Ferwana Ankur Mani Lav Varshney OOD 66 1 0 17 Dec 2021
FedDAG: Federated DAG Structure Learning Erdun Gao Junjia Chen Li Shen Tongliang Liu Biwei Huang H. Bondell FedML 87 17 0 07 Dec 2021
Learning Invariant Representations with Missing Data Mark Goldstein J. Jacobsen O. Chau A. Saporta A. Puli Rajesh Ranganath Andrew C. Miller OOD 59 5 0 01 Dec 2021
Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective Yuejiang Liu Riccardo Cadei Jonas Schweizer Sherwin Bahmani Alexandre Alahi OOD TTA 106 53 0 29 Nov 2021