Targeted VAE: Variational and Targeted Learning for Causal Inference

28 September 2020

Papers citing "Targeted VAE: Variational and Targeted Learning for Causal Inference"

28 / 28 papers shown

Title
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies Shachi Deshpande Kaiwen Wang Dhruv Sreenivas Zheng Li Volodymyr Kuleshov CML SyDa 57 11 0 18 Mar 2022
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 89 300 0 03 Mar 2021
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding Pengzhou (Abel) Wu Kenji Fukumizu CML 47 13 0 17 Jan 2021
Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models Andrew Jesson Sören Mindermann Uri Shalit Y. Gal CML 45 74 0 01 Jul 2020
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data Sindy Löwe David Madras R. Zemel Max Welling CML BDL AI4TS 90 131 0 18 Jun 2020
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks Ankit Sharma Garima Gupta Ranjitha Prasad Arnab Chatterjee Lovekesh Vig Gautam M. Shroff CML 31 7 0 28 Apr 2020
Decision-Making with Auto-Encoding Variational Bayes Romain Lopez Pierre Boyeau Nir Yosef Michael I. Jordan Jeffrey Regier BDL 303 10,591 0 17 Feb 2020
A Survey on Causal Inference Liuyi Yao Zhixuan Chu Sheng Li Yaliang Li Jing Gao Aidong Zhang CML 71 506 0 05 Feb 2020
Treatment effect estimation with disentangled latent factors Weijia Zhang Lin Liu Jiuyong Li CML 43 89 0 29 Jan 2020
Reducing Selection Bias in Counterfactual Reasoning for Individual Treatment Effects Estimation Zichen Zhang Qingfeng Lan Lei Ding Yue Wang Negar Hassanpour Russell Greiner BDL CML 49 9 0 19 Dec 2019
Demystifying Inter-Class Disentanglement Aviv Gabbay Yedid Hoshen DRL 36 56 0 27 Jun 2019
Learning Individual Causal Effects from Networked Observational Data Ruocheng Guo Wenlin Yao Huan Liu CML OOD 39 98 0 08 Jun 2019
Adapting Neural Networks for the Estimation of Treatment Effects Claudia Shi David M. Blei Victor Veitch CML 123 373 0 05 Jun 2019
Machine learning in policy evaluation: new tools for causal inference N. Kreif K. DiazOrdaz ELM CML 56 46 0 01 Mar 2019
On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives Alexander DÁmour CML 99 41 0 27 Feb 2019
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 111 1,466 0 29 Nov 2018
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 127 1,050 0 18 Oct 2018
Perfect Match: A Simple Method for Learning Representations For Counterfactual Inference With Neural Networks Patrick Schwab Lorenz Linhardt W. Karlen CML BDL 45 111 0 01 Oct 2018
Invariant Representations without Adversarial Training Daniel Moyer Shuyang Gao Rob Brekelmans Greg Ver Steeg Aram Galstyan OOD 51 210 0 24 May 2018
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 173 742 0 24 May 2017
Double/Debiased/Neyman Machine Learning of Treatment Effects Victor Chernozhukov Denis Chetverikov Mert Demirer E. Duflo Christian B. Hansen Whitney Newey CML FedML 118 351 0 30 Jan 2017
Deep Variational Information Bottleneck Alexander A. Alemi Ian S. Fischer Joshua V. Dillon Kevin Patrick Murphy 98 1,714 0 01 Dec 2016
Variational Inference: A Review for Statisticians David M. Blei A. Kucukelbir Jon D. McAuliffe BDL 227 4,778 0 04 Jan 2016
Recursive Partitioning for Heterogeneous Causal Effects Susan Athey Guido Imbens CML 162 1,428 0 05 Apr 2015
Deep Learning and the Information Bottleneck Principle Naftali Tishby Noga Zaslavsky DRL 161 1,580 0 09 Mar 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.4K 149,842 0 22 Dec 2014
Counterfactual Reasoning and Learning Systems Léon Bottou J. Peters J. Q. Candela Denis Xavier Charles D. M. Chickering Elon Portugaly Dipankar Ray Patrice Y. Simard Edward Snelson CML OffRL 288 783 0 11 Sep 2012
Identifiability of parameters in latent structure models with many observed variables E. Allman C. Matias J. Rhodes CML 151 533 0 29 Sep 2008