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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"

43 / 493 papers shown

Title
Causal Regularization M. T. Bahadori OOD CML 81 51 0 28 Jun 2019
Direct Learning with Guarantees of the Difference DAG Between Structural Equation Models Asish Ghoshal Kevin Bello Jean Honorio CML 43 8 0 28 Jun 2019
Neuropathic Pain Diagnosis Simulator for Causal Discovery Algorithm Evaluation Ruibo Tu Kun Zhang Bo Christer Bertilson Hedvig Kjellström Cheng Zhang OOD CML 91 43 0 04 Jun 2019
A Unifying Causal Framework for Analyzing Dataset Shift-stable Learning Algorithms Adarsh Subbaswamy Bryant Chen Suchi Saria OOD 57 18 0 27 May 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models Erdun Gao Kun Zhang Biwei Huang Clark Glymour CML AI4TS 84 64 0 26 May 2019
Causal Discovery with General Non-Linear Relationships Using Non-Linear ICA R. Monti Kun Zhang Aapo Hyvarinen CML 87 94 0 19 Apr 2019
Orthogonal Structure Search for Efficient Causal Discovery from Observational Data Anant Raj Luigi Gresele M. Besserve Bernhard Schölkopf Stefan Bauer CML 20 0 0 06 Mar 2019
Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes Erdun Gao Kun Zhang Jiji Zhang Joseph Ramsey Ruben Sanchez-Romero Clark Glymour Bernhard Schölkopf 92 230 0 05 Mar 2019
A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms Yoshua Bengio T. Deleu Nasim Rahaman Nan Rosemary Ke Sébastien Lachapelle O. Bilaniuk Anirudh Goyal C. Pal CML OOD 134 335 0 30 Jan 2019
Veridical Data Science Bin Yu Karl Kumbier 88 168 0 23 Jan 2019
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach Niklas Pfister Stefan Bauer J. Peters CML 43 41 0 28 Oct 2018
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 74 168 0 25 Sep 2018
The Deconfounded Recommender: A Causal Inference Approach to Recommendation Yixin Wang Dawen Liang Laurent Charlin David M. Blei CML 79 73 0 20 Aug 2018
Switching Regression Models and Causal Inference in the Presence of Discrete Latent Variables Rune Christiansen J. Peters CML 26 14 0 16 Aug 2018
Adaptive Skip Intervals: Temporal Abstraction for Recurrent Dynamical Models Alexander Neitz Giambattista Parascandolo Stefan Bauer Bernhard Schölkopf 83 38 0 14 Aug 2018
Semi-Generative Modelling: Covariate-Shift Adaptation with Cause and Effect Features Julius von Kügelgen A. Mey Marco Loog CML GAN 51 14 0 20 Jul 2018
Stable Prediction across Unknown Environments Kun Kuang Ruoxuan Xiong Peng Cui Susan Athey Bo Li OOD 93 167 0 16 Jun 2018
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise Niklas Pfister S. Weichwald Peter Buhlmann Bernhard Schölkopf OOD CML 58 16 0 04 Jun 2018
The Blessings of Multiple Causes Yixin Wang David M. Blei AI4CE CML 68 291 0 17 May 2018
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure Rajen Dinesh Shah J. Peters 180 302 0 19 Apr 2018
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions Karren D. Yang Abigail Katoff Caroline Uhler CML 79 103 0 17 Feb 2018
Discovering Markov Blanket from Multiple interventional Datasets Kui Yu Lin Liu Jiuyong Li 56 6 0 25 Jan 2018
Conditional Variance Penalties and Domain Shift Robustness C. Heinze-Deml N. Meinshausen OOD VLM 78 4 0 31 Oct 2017
Budgeted Experiment Design for Causal Structure Learning AmirEmad Ghassami Saber Salehkaleybar Negar Kiyavash Elias Bareinboim CML 107 64 0 11 Sep 2017
Estimation of interventional effects of features on prediction Patrick Blobaum Shohei Shimizu CML 29 8 0 03 Sep 2017
Two-sample instrumental variable analyses using heterogeneous samples Qingyuan Zhao Jingshu Wang J. Bowden Dylan S. Small 41 47 0 31 Aug 2017
Gradient Episodic Memory for Continual Learning David Lopez-Paz MarcÁurelio Ranzato VLM CLL 153 2,743 0 26 Jun 2017
Invariant Causal Prediction for Sequential Data Niklas Pfister Peter Buhlmann J. Peters OOD 80 122 0 25 Jun 2017
Learning Causal Structures Using Regression Invariance AmirEmad Ghassami Saber Salehkaleybar Negar Kiyavash Kun Zhang OOD CML 71 61 0 26 May 2017
Group invariance principles for causal generative models M. Besserve Naji Shajarisales Bernhard Schölkopf Dominik Janzing 74 49 0 05 May 2017
Cost-Optimal Learning of Causal Graphs Murat Kocaoglu A. Dimakis S. Vishwanath CML 127 68 0 08 Mar 2017
Optimal Experiment Design for Causal Discovery from Fixed Number of Experiments AmirEmad Ghassami Saber Salehkaleybar Negar Kiyavash CML 36 5 0 27 Feb 2017
Causal Discovery Using Proxy Variables Mateo Rojas-Carulla Marco Baroni David Lopez-Paz CML 63 15 0 23 Feb 2017
Causal Regularization M. T. Bahadori Krzysztof Chalupka Edward Choi Robert Chen Walter F. Stewart Jimeng Sun CML OOD 40 2 0 08 Feb 2017
Learning causal effects from many randomized experiments using regularized instrumental variables A. Peysakhovich Dean Eckles CML 112 23 0 04 Jan 2017
Causal Learning via Manifold Regularization S. Hill Chris J. Oates Duncan A. J. Blythe S. Mukherjee CML 21 1 0 16 Dec 2016
Joint Causal Inference from Multiple Contexts Joris M. Mooij Sara Magliacane Tom Claassen CML 140 15 0 30 Nov 2016
A Review on Algorithms for Constraint-based Causal Discovery Kui Yu Jiuyong Li Lin Liu AI4TS CML 46 22 0 12 Nov 2016
Ancestral Causal Inference Sara Magliacane Tom Claassen Joris M. Mooij CML 114 63 0 22 Jun 2016
Learning Optimal Interventions Jonas W. Mueller David N. Reshef George Du Tommi Jaakkola 38 9 0 16 Jun 2016
Structure Learning in Graphical Modeling Mathias Drton Marloes H. Maathuis CML 107 252 0 07 Jun 2016
Invariant Models for Causal Transfer Learning Mateo Rojas-Carulla Bernhard Schölkopf Richard Turner J. Peters OOD 86 23 0 19 Jul 2015
backShift: Learning causal cyclic graphs from unknown shift interventions Dominik Rothenhäusler C. Heinze J. Peters N. Meinshausen OOD 94 72 0 08 Jun 2015