juangamella / icpLinks
Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant prediction: identification and confidence intervals" by Jonas Peters, Peter Bühlmann and Nicolai Meinshausen.
☆23Updated last year
Alternatives and similar repositories for icp
Users that are interested in icp are comparing it to the libraries listed below
Sorting:
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆53Updated 4 years ago
- Causal Discovery from Nonstationary/Heterogeneous Data.☆53Updated 5 years ago
- ☆28Updated last year
- ☆32Updated 7 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
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated last year
- Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge☆27Updated 2 years ago
- ☆40Updated 6 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆62Updated 4 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
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆76Updated 3 years ago
- ☆96Updated 2 years ago
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 4 years ago
- pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆70Updated 4 years ago
- Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality☆36Updated 4 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- ☆23Updated 3 years ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆75Updated 10 months ago
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Updated 5 years ago
- A generalized score-based method for Causal Discovery☆17Updated 4 years ago
- Python code of Hilbert-Schmidt Independence Criterion☆88Updated 3 years ago
- Implementation of the Latent CCM paper☆16Updated last year
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- Method based on neural networks and variational inference for causal discovery under latent interventions, i. e. learning a shared causal…☆19Updated 3 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 3 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆23Updated 6 years ago
- python code for kernel methods☆41Updated 6 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆154Updated 2 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆101Updated 4 years ago