AliciaCurth / CATENetsLinks
Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
β154Updated last year
Alternatives and similar repositories for CATENets
Users that are interested in CATENets are comparing it to the libraries listed below
Sorting:
- ππ Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatmβ¦β94Updated 2 years ago
- Counterfactual Regressionβ319Updated 3 years ago
- Example causal datasets with consistent formatting and ground truthβ105Updated 9 months ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorfloβ¦β345Updated last year
- β289Updated 3 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed causβ¦β86Updated 4 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring codeβ84Updated 7 years ago
- Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018β67Updated 5 years ago
- A data index for learning causality.β484Updated 2 years ago
- Causal Effect Inference with Deep Latent-Variable Modelsβ354Updated 5 years ago
- ββ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.β131Updated 2 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)β50Updated 6 years ago
- CPDAG Estimation using PC-Algorithmβ96Updated 3 years ago
- Non-parametrics for Causal Inferenceβ50Updated 3 years ago
- Must-read papers and resources related to causal inference and machine (deep) learningβ750Updated 3 years ago
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrβ¦β139Updated 2 years ago
- Counterfactual Regressionβ25Updated 9 years ago
- BITES: Balanced Individual Treatment Effect for Survival dataβ19Updated 2 years ago
- β36Updated 4 months ago
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bicaβ¦β30Updated 5 years ago
- DAGs with NO TEARS: Continuous Optimization for Structure Learningβ667Updated last year
- EconML/CausalML KDD 2021 Tutorialβ167Updated 2 years ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Pythonβ67Updated last year
- [Experimental] Global causal discovery algorithmsβ113Updated 3 weeks ago
- Makes algorithms/code in Tetrad available in Python via JPypeβ91Updated this week
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Searchβ¦β62Updated 11 months ago
- β205Updated 2 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)β63Updated 5 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Predictionβ161Updated 4 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. Bβ¦β67Updated last year