ioanabica / Counterfactual-Recurrent-NetworkLinks
Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. Bica, A. M. Alaa, J. Jordon, M. van der Schaar
☆59Updated last year
Alternatives and similar repositories for Counterfactual-Recurrent-Network
Users that are interested in Counterfactual-Recurrent-Network are comparing it to the libraries listed below
Sorting:
- ☆40Updated 6 years ago
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 3 years ago
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- Source code for a comprehensive analysis of MTL over EHR timeseries data.☆37Updated 2 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆61Updated 5 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆88Updated 2 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆31Updated 5 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 6 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆129Updated 2 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆60Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Repository for Deep Structural Causal Models for Tractable Counterfactual Inference☆282Updated 2 years ago
- ☆28Updated last year
- An Empirical Framework for Domain Generalization In Clinical Settings☆31Updated 3 years ago
- Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.☆131Updated 4 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated 11 months ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆56Updated 2 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Clairvoyance: a Unified, End-to-End AutoML Pipeline for Medical Time Series☆132Updated 2 years ago
- A benchmark for distribution shift in tabular data☆54Updated last year
- This repository contains the code used for Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care …☆79Updated 2 months ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- Experiments applying FIDDLE on MIMIC-III and eICU. https://doi.org/10.1093/jamia/ocaa139☆25Updated 3 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 3 years ago
- ☆93Updated 2 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago