MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models

25 February 2020

Papers citing "MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable Models"

10 / 10 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 60 11 0 18 Mar 2022
On the consistency of supervised learning with missing values Julie Josse Jacob M. Chen Nicolas Prost Erwan Scornet Gaël Varoquaux 57 115 0 19 Feb 2019
A Survey of Learning Causality with Data: Problems and Methods Ruocheng Guo Lu Cheng Jundong Li P. R. Hahn Huan Liu CML 56 168 0 25 Sep 2018
Causal Inference with Noisy and Missing Covariates via Matrix Factorization Nathan Kallus Xiaojie Mao Madeleine Udell CML 50 63 0 03 Jun 2018
Causal Effect Inference with Deep Latent-Variable Models Christos Louizos Uri Shalit Joris Mooij David Sontag R. Zemel Max Welling CML BDL 181 741 0 24 May 2017
Generalized Random Forests Susan Athey J. Tibshirani Stefan Wager 258 1,357 0 05 Oct 2016
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 271 729 0 12 May 2016
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests Stefan Wager Susan Athey SyDa CML 284 2,483 0 14 Oct 2015
Matrix Completion and Low-Rank SVD via Fast Alternating Least Squares Trevor Hastie Rahul Mazumder Jason D. Lee R. Zadeh 135 525 0 09 Oct 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 420 16,944 0 20 Dec 2013