ioanabica / Time-Series-DeconfounderLinks
Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. Bica, A. M. Alaa, M. van der Schaar
☆52Updated 4 years ago
Alternatives and similar repositories for Time-Series-Deconfounder
Users that are interested in Time-Series-Deconfounder are comparing it to the libraries listed below
Sorting:
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- ☆40Updated 6 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 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
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 3 years ago
- ☆28Updated last year
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆88Updated 2 years ago
- Causal Discovery from Nonstationary/Heterogeneous Data.☆53Updated 4 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆60Updated 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
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…☆30Updated 4 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆61Updated 5 years ago
- ☆61Updated 4 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality☆35Updated 4 years ago
- AC_TPC: Temporal Phenotyping using Deep Predicting Clustering of Disease Progression☆46Updated 4 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
- pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆70Updated 4 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- Codebase for INVASE: Instance-wise Variable Selection - 2019 ICLR☆62Updated 5 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…☆21Updated 3 years ago
- This repository contains the implementation of Dynamask, a method to identify the features that are salient for a model to issue its pred…☆76Updated 3 years ago
- ☆93Updated 2 years ago
- Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge☆27Updated 2 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆129Updated 2 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 2 years ago
- ☆91Updated 3 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
- Codebase for "Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions", ICML 2020.☆9Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago