christinaheinze / nonlinearICP-and-CondIndTestsLinks
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
Sorting:
- Conditional calibration of conformal p-values for outlier detection.☆36Updated 2 years ago
- ☆32Updated 7 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 to reproduce the numerical experiments in the paper Domain adaptation under structural causal models by Yuansi Chen and Peter Bühlma…☆18Updated 4 years ago
- Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831☆36Updated 2 years ago
- Uncertainty in Conditional Average Treatment Effect Estimation☆33Updated 4 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆62Updated 4 years ago
- python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.☆25Updated 2 years ago
- (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’☆31Updated 2 years ago
- Non-parametrics for Causal Inference☆49Updated 3 years ago
- ☆18Updated last year
- ☆40Updated 6 years ago
- Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code☆84Updated 7 years ago
- Approximate knockoffs and model-free variable selection.☆55Updated 3 years ago
- ☆11Updated 7 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆77Updated 4 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 5 years ago
- Scalable open-source software to run, develop, and benchmark causal discovery algorithms☆72Updated this week
- TIme series DiscoverY BENCHmark (tidybench)☆38Updated last year
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆100Updated 6 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆152Updated 2 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆23Updated 6 years ago
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- A lightweight implementation of removal-based explanations for ML models.☆58Updated 4 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Causal Inference & Deep Learning, MIT IAP 2018☆88Updated 7 years ago
- A decision-tree based conditional independence test.☆34Updated 2 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆60Updated last year
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆157Updated 4 years ago
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆23Updated last year