Sequential Deconfounding for Causal Inference with Unobserved Confounders

16 April 2021

Papers citing "Sequential Deconfounding for Causal Inference with Unobserved Confounders"

9 / 9 papers shown

Title
Stabilized Neural Prediction of Potential Outcomes in Continuous Time Konstantin Hess Stefan Feuerriegel 46 0 0 04 Oct 2024
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 58 2 0 16 Oct 2023
Estimating Treatment Effects in Continuous Time with Hidden Confounders Defu Cao James Enouen Y. Liu CML 24 2 0 19 Feb 2023
Learning Optimal Dynamic Treatment Regimes Using Causal Tree Methods in Medicine Theresa Blümlein Joel Persson Stefan Feuerriegel CML 22 11 0 14 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 34 54 0 31 Mar 2022
Combining Observational and Randomized Data for Estimating Heterogeneous Treatment Effects Tobias Hatt Jeroen Berrevoets Alicia Curth Stefan Feuerriegel M. Schaar CML 42 29 0 25 Feb 2022
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies Milan Kuzmanovic Tobias Hatt Stefan Feuerriegel CML 42 21 0 06 Dec 2021
Estimating Average Treatment Effects via Orthogonal Regularization Tobias Hatt Stefan Feuerriegel CML 148 35 0 21 Jan 2021
Learning Representations for Counterfactual Inference Fredrik D. Johansson Uri Shalit David Sontag CML OOD BDL 210 719 0 12 May 2016