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.
☆22Updated 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 ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- ☆40Updated 6 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated 11 months ago
- ☆32Updated 7 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 2 years ago
- ☆28Updated last year
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆60Updated 4 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality☆35Updated 4 years ago
- pyCausalFS:A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆70Updated 4 years ago
- Discovering directional relations via minimum predictive information regularization☆24Updated 5 years ago
- Code for `BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery`, Neurips 2021☆26Updated 3 years ago
- Causal Discovery from Nonstationary/Heterogeneous Data.☆53Updated 4 years ago
- Code for paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge☆27Updated 2 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆23Updated 5 years ago
- Causal inference is a critical task in various fields such as healthcare,economics, marketing and education. Recently, there have beensig…☆21Updated 3 years ago
- Code for TEDVAE, a VAE-based treatment effect estimation algorithm.☆25Updated 2 years ago
- ☆61Updated 4 years ago
- ☆93Updated 2 years ago
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Updated 5 years ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆74Updated 8 months ago
- A generalized score-based method for Causal Discovery☆17Updated 4 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆43Updated 7 months ago
- An encoder-decoder framework for learning from incomplete data☆45Updated 2 years ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆31Updated 5 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Code for NeurIPS 2020 paper: "Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks" by I. Bica…☆30Updated 4 years ago
- Implementation of the MIWAE method for deep generative modelling of incomplete data sets.☆41Updated last year
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆75Updated 4 years ago