caus-am / jci
Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)
☆15Updated 4 years ago
Related projects ⓘ
Alternatives and complementary repositories for jci
- A unified interface for the estimation of causal networks☆22Updated 4 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆147Updated last year
- Adjustment Identification Distance: A gadjid for Causal Structure Learning☆9Updated 3 months ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆72Updated 2 years ago
- Non-parametrics for Causal Inference☆43Updated 2 years ago
- Causal Modeling with Stationary Diffusions, AISTATS 2024☆15Updated 3 months ago
- Code to run submissions for the Atlantic Causal Inference Competition☆41Updated 2 months ago
- ☆21Updated 11 months ago
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Updated 4 years ago
- Code to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 3 years ago
- Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https:…☆15Updated last year
- A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…☆102Updated 9 months ago
- Nonlinear Causal Discovery with Confounders☆14Updated last year
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 3 years ago
- Approximate knockoffs and model-free variable selection.☆51Updated 3 years ago
- A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.☆64Updated this week
- Code for the paper "Local Causal Discovery for Estimating Causal Effects".☆7Updated 7 months ago
- Short tutorials on the use of machine learning methods for causal inference☆48Updated last year
- Example causal datasets with consistent formatting and ground truth☆66Updated last year
- Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"☆79Updated 7 months ago
- ☆92Updated 10 months ago
- Amortized Inference for Causal Structure Learning, NeurIPS 2022☆54Updated 7 months ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆68Updated 3 years ago
- A decision-tree based conditional independence test.☆34Updated last year
- Python package for (conditional) independence testing and statistical functions related to causality.☆22Updated last month
- CSuite: A Suite of Benchmark Datasets for Causality☆58Updated last year
- Dataset repository for the 2024 paper "The Causal Chambers: Real Physical Systems as a Testbed for AI Methodology" by Juan L. Gamella, Jo…☆23Updated this week
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated 8 months ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆80Updated 6 years ago
- A deep-learning-based conditional independence test that works for big, high-dimensional data.☆14Updated 7 years ago