blei-lab / deconfounder_public
☆20Updated 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
- ☆87Updated 5 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆74Updated 4 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆156Updated 3 years ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"☆56Updated 2 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 8 months ago
- ☆38Updated 6 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆83Updated 6 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆58Updated last year
- CSuite: A Suite of Benchmark Datasets for Causality☆67Updated last year
- ☆29Updated last year
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆137Updated 9 months ago
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated last year
- ☆22Updated 3 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Example causal datasets with consistent formatting and ground truth☆82Updated last year
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 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
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…☆29Updated 4 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆81Updated 3 months ago
- ☆76Updated 4 years ago
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated 2 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆101Updated 3 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 6 years ago
- ☆16Updated 8 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆87Updated 2 years ago
- Reimplementation of NOTEARS in Tensorflow☆35Updated 2 years ago
- Some notes on Causal Inference, with examples in python☆153Updated 5 years ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆56Updated 10 months ago