christinaheinze / nonlinearICP-and-CondIndTests
Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents of a given target variable from data collected in different experimental or environmental conditions, extending 'Invariant Causal Prediction' from Peters, Buehlmann and Meinshausen (2016) to nonlinear settings…
☆17Updated 5 years ago
Alternatives and similar repositories for nonlinearICP-and-CondIndTests:
Users that are interested in nonlinearICP-and-CondIndTests are comparing it to the libraries listed below
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 4 years ago
- ☆12Updated 7 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
- python code for kernel methods☆38Updated 6 years ago
- A unified interface for the estimation of causal networks☆22Updated 5 years ago
- ☆32Updated 6 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated 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
- Uncertainty in Conditional Average Treatment Effect Estimation☆31Updated 4 years ago
- This packages provides a simple python implementation of Invariant Causal Prediction (ICP)☆13Updated last year
- ☆22Updated last year
- Material for the practical of the DS3 course on "Representing and comparing probabilities with kernels"☆26Updated 6 years ago
- ☆38Updated 6 years ago
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆21Updated last year
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code to reproduce the experimental results from the paper "Active Invariant Causal Prediction: Experiment Selection Through Stability", b…☆20Updated last year
- Demo data and code for "Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding".☆26Updated 3 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- Approximate knockoffs and model-free variable selection.☆54Updated 3 years ago
- python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.☆25Updated 2 years ago
- Code for "Towards a learning theory of cause-effect inference" (ICML 2015).☆29Updated 4 years ago
- Non-parametrics for Causal Inference☆44Updated 3 years ago
- Causal Discovery with Equal Variance Assumption☆9Updated 2 years ago
- Structural Causal Bandit☆24Updated 3 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 8 months ago
- Continuous-time Markov model with discrete observations☆11Updated 9 years ago
- ☆35Updated 5 years ago
- References for Papers at the Intersection of Causality and Fairness☆18Updated 6 years ago