kjchalup / independence_test
A deep-learning-based conditional independence test that works for big, high-dimensional data.
☆14Updated 7 years ago
Alternatives and similar repositories for independence_test:
Users that are interested in independence_test are comparing it to the libraries listed below
- A decision-tree based conditional independence test.☆34Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- Python package for the creation, manipulation, and learning of Causal DAGs☆152Updated 2 years ago
- The Randomized Conditional Independence Test (RCIT) and the Randomized conditional Correlation Test (RCoT)☆25Updated 5 years ago
- python code for kernel methods☆38Updated 6 years ago
- Code for the paper "Joint Causal Inference from Multiple Contexts" (JMLR 2020)☆16Updated 4 years ago
- A unified interface for the estimation of causal networks☆22Updated 5 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
- Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing☆45Updated last year
- ☆87Updated 5 years ago
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated last year
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Updated 5 years ago
- Code for ICLR 2020 paper: "Estimating counterfactual treatment outcomes over time through adversarially balanced representations" by I. B…☆59Updated last year
- Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)☆50Updated 6 years ago
- ☆12Updated 7 years ago
- General Latent Feature Modeling for Heterogeneous data☆48Updated last year
- Hierarchical Change-Point Detection☆14Updated 6 years ago
- Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds☆11Updated 5 years ago
- This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https…☆35Updated 7 months ago
- The holdout randomization test: feature selection using black box predictive models☆22Updated 4 years ago
- On the Role of Sparsity and DAG Constraints for Learning Linear DAGs☆33Updated 3 years ago
- Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"☆99Updated 5 years ago
- Framework to generate observational and interventional samples from structural equation models (SEMs)☆15Updated last week
- The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).☆58Updated 2 years ago
- Approximate knockoffs and model-free variable selection.☆54Updated 3 years ago
- Kaggle's Causality Challenge Solution for team FirfiD☆26Updated 11 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆74Updated 4 years ago
- ☆18Updated 5 years ago
- CPDAG Estimation using PC-Algorithm☆96Updated 3 years ago
- Repository for "Differentiable Causal Discovery from Interventional Data"☆74Updated 3 years ago