bradyneal / realcauseLinks
Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed causal structure.
☆75Updated 4 years ago
Alternatives and similar repositories for realcause
Users that are interested in realcause are comparing it to the libraries listed below
Sorting:
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆64Updated 3 months ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆75Updated 3 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆140Updated 11 months ago
- CSuite: A Suite of Benchmark Datasets for Causality☆67Updated 2 years ago
- Example causal datasets with consistent formatting and ground truth☆83Updated last month
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- [Experimental] Global causal discovery algorithms☆101Updated 3 months ago
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆82Updated last year
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆119Updated last year
- DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021☆50Updated last year
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆30Updated 5 years ago
- Reimplementation of NOTEARS in Tensorflow☆33Updated 2 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 2 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆152Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Non-parametrics for Causal Inference☆47Updated 3 years ago
- ☆39Updated 6 years ago
- 💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…☆88Updated 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 9 months ago
- Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…☆59Updated 3 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆44Updated last year
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 3 years ago
- Public dataset repository for the Causal Chamber Project☆40Updated last month
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆69Updated this week
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆81Updated 5 months ago
- Short tutorials on the use of machine learning methods for causal inference☆49Updated 2 years ago
- ☆78Updated 4 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆49Updated 6 years ago
- A curated list of awesome work on causal inference, particularly in machine learning.☆105Updated 4 years ago