blei-lab / deconfounder_publicLinks
☆22Updated 2 years ago
Alternatives and similar repositories for deconfounder_public
Users that are interested in deconfounder_public are comparing it to the libraries listed below
Sorting:
- 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
- ☆87Updated 5 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆143Updated last year
- Short tutorials on the use of machine learning methods for causal inference☆48Updated 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
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆157Updated 4 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆90Updated 2 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
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆57Updated 2 years ago
- ☆40Updated 6 years ago
- ☆11Updated 7 years ago
- An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…☆14Updated last year
- ➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.☆130Updated 2 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
- References for Papers at the Intersection of Causality and Fairness☆18Updated 6 years ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- ☆39Updated 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
- Example causal datasets with consistent formatting and ground truth☆87Updated 4 months ago
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Materials for STAT 991: Topics In Modern Statistical Learning (UPenn, 2022 Spring) - uncertainty quantification, conformal prediction, ca…☆176Updated last year
- ☆24Updated 3 years ago
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- ☆18Updated last year
- Counterfactual Regression☆313Updated 2 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆107Updated 4 years ago