Counterfactual regression (CFR) by learning balanced representations, as developed by Johansson, Shalit & Sontag (2016) and Shalit, Johansson & Sontag (2016). cfrnet is implemented in Python using TensorFlow 0.12.0-rc1 and NumPy 1.11.3. The code has not been tested with TensorFlow 1.0. The source project at CFRNET
This repository,based on Python and Tensorflow,accompanies the semi-synthetic simulations conducted in the paper "Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models" by Yuta Saito and Shota Yasui, which has been accepted by ICML2020.
The source project at Counterfactual-Cv
This repository,based on Python and Tensorflow,achieve experiments conducted in the paper "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar in International Conference on Machine Learning (ICML) 2020
The source project at Time-Series-Deconfounder-Cv
This repository,based on Python and Tensorflow,achieve experiments conducted in the paper "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar in International Conference on Learning Representations (ICLR) 2020
The source project at Counterfactual-Recurrent-Network
This repository,based on Python and Tensorflow,achieve experiments conducted in the paper "Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks" by Bryan Lim, Ahmed Alaa and Mihaela van der Schaar, NeurIPS 2018
The source project at RMSN