The Blessings of Multiple Causes

17 May 2018

Papers citing "The Blessings of Multiple Causes"

38 / 38 papers shown

Title
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes V. Chauhan Lei A. Clifton Gaurav Nigam David A. Clifton CML 63 0 0 12 Feb 2025
Substitute adjustment via recovery of latent variables Jeffrey Adams Niels Richard Hansen CML 24 1 0 01 Mar 2024
Instrumental Variable Estimation for Causal Inference in Longitudinal Data with Time-Dependent Latent Confounders Debo Cheng Ziqi Xu Jiuyong Li Lin Liu Jixue Liu Wentao Gao T. Le CML 38 6 0 12 Dec 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 68 2 0 16 Oct 2023
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding Alizée Pace Hugo Yèche Bernhard Schölkopf Gunnar Rätsch Guy Tennenholtz OffRL 16 6 0 01 Jun 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders Defu Cao James Enouen Yong-Jin Liu CML 35 2 0 19 Feb 2023
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations Nabeel Seedat F. Imrie Alexis Bellot Zhaozhi Qian M. Schaar OOD CML 29 52 0 16 Jun 2022
Causal Inference from Small High-dimensional Datasets Raquel Y. S. Aoki Martin Ester CML 21 4 0 19 May 2022
Hybrid Feature- and Similarity-Based Models for Joint Prediction and Interpretation Jacqueline K. Kueper J. Rayner D. Lizotte 13 2 0 12 Apr 2022
Scientometric Review of Artificial Intelligence for Operations & Maintenance of Wind Turbines: The Past, Present and Future Joyjit Chatterjee Nina Dethlefs 26 83 0 30 Mar 2022
Estimating Social Influence from Observational Data Dhanya Sridhar Caterina De Bacco David M. Blei 19 3 0 24 Mar 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 47 29 0 25 Feb 2022
Correcting Confounding via Random Selection of Background Variables You-Lin Chen Lenon Minorics Dominik Janzing CML 27 4 0 04 Feb 2022
Deep Causal Reasoning for Recommendations Yaochen Zhu Jing Yi Jiayi Xie Zhenzhong Chen CML BDL 27 10 0 06 Jan 2022
Multi-treatment Effect Estimation from Biomedical Data Raquel Y. S. Aoki Yizhou Chen M. Ester 13 0 0 14 Dec 2021
Causal Knowledge Guided Societal Event Forecasting Songgaojun Deng Huzefa Rangwala Yue Ning AI4TS 24 2 0 10 Dec 2021
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 28 34 0 27 Oct 2021
Deconfounded Causal Collaborative Filtering Shuyuan Xu Juntao Tan Shelby Heinecke Jia Li Yongfeng Zhang CML 35 40 0 14 Oct 2021
Effects of Multi-Aspect Online Reviews with Unobserved Confounders: Estimation and Implication Lu Cheng Ruocheng Guo K. S. Candan Huan Liu CML 21 6 0 04 Oct 2021
Towards Principled Causal Effect Estimation by Deep Identifiable Models Pengzhou (Abel) Wu Kenji Fukumizu BDL OOD CML 27 3 0 30 Sep 2021
Desiderata for Representation Learning: A Causal Perspective Yixin Wang Michael I. Jordan CML 32 80 0 08 Sep 2021
DoGR: Disaggregated Gaussian Regression for Reproducible Analysis of Heterogeneous Data N. Alipourfard Keith Burghardt Kristina Lerman 14 0 0 31 Aug 2021
Sample Observed Effects: Enumeration, Randomization and Generalization Andre F. Ribeiro CML 16 4 0 09 Aug 2021
Obtaining Causal Information by Merging Datasets with MAXENT Sergio Hernan Garrido Mejia Elke Kirschbaum Dominik Janzing CML 18 9 0 15 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
What can the millions of random treatments in nonexperimental data reveal about causes? Andre F. Ribeiro Frank Neffke Ricardo Hausmann CML 20 1 0 03 May 2021
The Blessings of Unlabeled Background in Untrimmed Videos Yuan Liu Jingyuan Chen Zhenfang Chen Bing Deng Jianqiang Huang Hanwang Zhang CML 31 43 0 24 Mar 2021
NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments S. Parbhoo Stefan Bauer Patrick Schwab CML BDL 11 16 0 20 Mar 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 37 296 0 03 Mar 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 35 104 0 03 Nov 2020
Naïve regression requires weaker assumptions than factor models to adjust for multiple cause confounding Justin Grimmer D. Knox Brandon M Stewart CML 8 12 0 24 Jul 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 28 178 0 11 Jun 2020
Ivy: Instrumental Variable Synthesis for Causal Inference Zhaobin Kuang Frederic Sala N. Sohoni Sen Wu A. Córdova-Palomera Jared A. Dunnmon J. Priest Christopher Ré CML 11 26 0 11 Apr 2020
Adapting Text Embeddings for Causal Inference Victor Veitch Dhanya Sridhar David M. Blei CML 9 21 0 29 May 2019
The Medical Deconfounder: Assessing Treatment Effects with Electronic Health Records Linying Zhang Yixin Wang A. Ostropolets J. J. Mulgrave David M. Blei G. Hripcsak BDL CML 15 1 0 03 Apr 2019
On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives Alexander DÁmour CML 14 41 0 27 Feb 2019
Using Embeddings to Correct for Unobserved Confounding in Networks Victor Veitch Yixin Wang David M. Blei CML 13 56 0 11 Feb 2019
Structural Agnostic Modeling: Adversarial Learning of Causal Graphs Diviyan Kalainathan Olivier Goudet Isabelle M Guyon David Lopez-Paz Michèle Sebag CML 24 93 0 13 Mar 2018