IBM-HRL-MLHLS / IBM-Causal-Inference-Benchmarking-FrameworkLinks
Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code
☆84Updated 7 years ago
Alternatives and similar repositories for IBM-Causal-Inference-Benchmarking-Framework
Users that are interested in IBM-Causal-Inference-Benchmarking-Framework are comparing it to the libraries listed below
Sorting:
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆91Updated 2 years ago
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆130Updated 2 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018☆62Updated 5 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
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆157Updated 4 years ago
- ☆40Updated 6 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆62Updated 4 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Non-parametrics for Causal Inference☆49Updated 3 years ago
- Counterfactual Regression☆313Updated 2 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 4 years ago
- ☆205Updated 2 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated last year
- Causal Effect Inference with Deep Latent-Variable Models☆345Updated 5 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
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆60Updated last year
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- ☆280Updated 3 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- Example causal datasets with consistent formatting and ground truth☆89Updated 5 months ago
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- A curated list of awesome work on causal inference, particularly in machine learning.☆108Updated 4 years ago
- ☆59Updated 3 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- EconML/CausalML KDD 2021 Tutorial☆162Updated 2 years ago