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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
Towards Principled Disentanglement for Domain Generalization Hanlin Zhang Yi-Fan Zhang Weiyang Liu Adrian Weller Bernhard Schölkopf Eric Xing OOD 126 118 0 27 Nov 2021
Understanding and Testing Generalization of Deep Networks on Out-of-Distribution Data Rui Hu Jitao Sang Jinqiang Wang Rui Hu Chaoquan Jiang CML OOD 59 7 0 17 Nov 2021
A Theoretical Analysis on Independence-driven Importance Weighting for Covariate-shift Generalization Renzhe Xu Xingxuan Zhang Zheyan Shen Tong Zhang Peng Cui OOD 80 26 0 03 Nov 2021
Identifying and Benchmarking Natural Out-of-Context Prediction Problems David Madras D. Psaltis CML OOD 105 4 0 25 Oct 2021
Learning Representations that Support Robust Transfer of Predictors Yilun Xu Tommi Jaakkola OOD 42 26 0 19 Oct 2021
Invariant Language Modeling Maxime Peyrard Sarvjeet Ghotra Martin Josifoski Vidhan Agarwal Barun Patra Dean Carignan Emre Kıcıman Robert West 92 13 0 16 Oct 2021
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction Guillaume Martinet Alexander Strzalkowski Barbara E. Engelhardt BDL OOD 46 7 0 13 Oct 2021
Gated Information Bottleneck for Generalization in Sequential Environments Francesco Alesiani Shujian Yu Xi Yu OOD AAML 56 13 0 12 Oct 2021
Stable Prediction on Graphs with Agnostic Distribution Shift Shengyu Zhang Kun Kuang J. Qiu Jin Yu Zhou Zhao Hongxia Yang Zhongfei Zhang Leilei Gan OOD 117 8 0 08 Oct 2021
The Connection between Out-of-Distribution Generalization and Privacy of ML Models Divyat Mahajan Shruti Tople Amit Sharma OOD 112 7 0 07 Oct 2021
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication Lu Cheng Ruocheng Guo K. S. Candan Huan Liu CML 55 6 0 04 Oct 2021
Optimization-based Causal Estimation from Heterogenous Environments Mingzhang Yin Yixin Wang David M. Blei OOD 123 18 0 24 Sep 2021
On the Impact of Spurious Correlation for Out-of-distribution Detection Yifei Ming Hang Yin Yixuan Li OODD 194 75 0 12 Sep 2021
Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization Alexandre Ramé Corentin Dancette Matthieu Cord OOD 139 209 0 07 Sep 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 121 44 0 06 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond Amir Feder Katherine A. Keith Emaad A. Manzoor Reid Pryzant Dhanya Sridhar ... Roi Reichart Margaret E. Roberts Brandon M Stewart Victor Veitch Diyi Yang CML 111 244 0 02 Sep 2021
A Subsampling-Based Method for Causal Discovery on Discrete Data Austin V. Goddard Yu Xiang CML 59 0 0 31 Aug 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 168 536 0 31 Aug 2021
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing Sindhu C. M. Gowda Shalmali Joshi Haoran Zhang Marzyeh Ghassemi CML 94 8 0 27 Aug 2021
Too Many, Too Improbable: testing joint hypotheses and closed testing shortcuts Phillip B. Mogensen B. Markussen 68 1 0 10 Aug 2021
Sample Observed Effects: Enumeration, Randomization and Generalization Andre F. Ribeiro CML 38 4 0 09 Aug 2021
Federated Causal Inference in Heterogeneous Observational Data Ruoxuan Xiong Allison Koenecke Michael A. Powell Zhu Shen Joshua T. Vogelstein Susan Athey FedML CML 74 48 0 25 Jul 2021
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 80 72 0 22 Jul 2021
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain Lukas Schott Julius von Kügelgen Frederik Trauble Peter V. Gehler Chris Russell Matthias Bethge Bernhard Schölkopf Francesco Locatello Wieland Brendel OOD DRL 128 74 0 17 Jul 2021
Obtaining Causal Information by Merging Datasets with MAXENT Sergio Hernan Garrido Mejia Elke Kirschbaum Dominik Janzing CML 119 10 0 15 Jul 2021
Source-Free Adaptation to Measurement Shift via Bottom-Up Feature Restoration Cian Eastwood I. Mason Christopher K. I. Williams Bernhard Schölkopf TTA 70 53 0 12 Jul 2021
Which Invariance Should We Transfer? A Causal Minimax Learning Approach Mingzhou Liu Xiangyu Zheng Xinwei Sun Fang Fang Yizhou Wang OOD 47 2 0 05 Jul 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 83 57 0 02 Jul 2021
Distributionally Robust Learning with Stable Adversarial Training Jiashuo Liu Zheyan Shen Peng Cui Linjun Zhou Kun Kuang Yangqiu Song OOD 35 12 0 30 Jun 2021
Finding Valid Adjustments under Non-ignorability with Minimal DAG Knowledge Abhin Shah Karthikeyan Shanmugam Kartik Ahuja CML 69 13 0 22 Jun 2021
Iterative Feature Matching: Toward Provable Domain Generalization with Logarithmic Environments Yining Chen Elan Rosenfeld Mark Sellke Tengyu Ma Andrej Risteski OOD 76 33 0 18 Jun 2021
Learning Stable Classifiers by Transferring Unstable Features Yujia Bao Shiyu Chang Regina Barzilay OOD 69 8 0 15 Jun 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 84 48 0 14 Jun 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja Ethan Caballero Dinghuai Zhang Jean-Christophe Gagnon-Audet Yoshua Bengio Ioannis Mitliagkas Irina Rish OOD 71 270 0 11 Jun 2021
Independent mechanism analysis, a new concept? Luigi Gresele Julius von Kügelgen Vincent Stimper Bernhard Schölkopf M. Besserve CML 100 102 0 09 Jun 2021
Operationalizing Complex Causes: A Pragmatic View of Mediation Limor Gultchin David S. Watson Matt J. Kusner Ricardo M. A. Silva CML 69 5 0 09 Jun 2021
Towards a Theoretical Framework of Out-of-Distribution Generalization Haotian Ye Chuanlong Xie Tianle Cai Ruichen Li Zhenguo Li Liwei Wang OODD OOD 123 112 0 08 Jun 2021
Searching for consistent associations with a multi-environment knockoff filter Shuangning Li Matteo Sesia Yaniv Romano Emmanuel Candès C. Sabatti 59 13 0 08 Jun 2021
Counterfactual Maximum Likelihood Estimation for Training Deep Networks Xinyi Wang Wenhu Chen Michael Stephen Saxon Wenjie Wang OOD CML BDL 84 8 0 07 Jun 2021
An Information-theoretic Approach to Distribution Shifts Marco Federici Ryota Tomioka Patrick Forré OOD 90 20 0 07 Jun 2021
Quantifying and Improving Transferability in Domain Generalization Guojun Zhang Han Zhao Yaoliang Yu Pascal Poupart 91 39 0 07 Jun 2021
Can Subnetwork Structure be the Key to Out-of-Distribution Generalization? Dinghuai Zhang Kartik Ahuja Yilun Xu Yisen Wang Aaron Courville OOD 97 96 0 05 Jun 2021
Sample Selection Bias in Evaluation of Prediction Performance of Causal Models J. P. Long M. Ha CML 23 6 0 03 Jun 2021
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms Yunqi Wang Furui Liu Zhitang Chen Qing Lian Guangyong Chen Jianye Hao Yik-Chung Wu OOD CML 72 35 0 02 Jun 2021
Invariant Policy Learning: A Causal Perspective Sorawit Saengkyongam Nikolaj Thams J. Peters Niklas Pfister CML OffRL 60 15 0 01 Jun 2021
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests Victor Veitch Alexander DÁmour Steve Yadlowsky Jacob Eisenstein OOD 80 93 0 31 May 2021
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers Yujia Bao Shiyu Chang Regina Barzilay 74 21 0 26 May 2021
Statistical Testing under Distributional Shifts Nikolaj Thams Sorawit Saengkyongam Niklas Pfister J. Peters OOD 113 10 0 22 May 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey Anton Van Den Hengel 113 90 0 12 May 2021
Causal Learning for Socially Responsible AI Lu Cheng Ahmadreza Mosallanezhad Paras Sheth Huan Liu 124 13 0 25 Apr 2021