babylonhealth / TwinNetworks
A library for handling Structural Causal Models and performing interventional and counterfactual inference on them.
☆10Updated 4 years ago
Alternatives and similar repositories for TwinNetworks:
Users that are interested in TwinNetworks are comparing it to the libraries listed below
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆59Updated 4 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 paper: NTS-NOTEARS: Learning Nonparametric DBNs With Prior Knowledge☆23Updated 2 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆22Updated 5 years ago
- Python implementation of the Invariant Causal Prediction (ICP) algorithm, from the 2015 paper "Causal inference using invariant predictio…☆20Updated last year
- Code for the paper "Estimating Transfer Entropy via Copula Entropy"☆40Updated last year
- TIme series DiscoverY BENCHmark (tidybench)☆37Updated last year
- ☆11Updated 2 years ago
- ☆29Updated 6 years ago
- Statistical Recurrent Unit based time series generative models for detecting nonlinear Granger causality☆33Updated 4 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆59Updated 7 months ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 2 years ago
- Code for the Structural Agnostic Model (https://arxiv.org/abs/1803.04929)☆52Updated 4 years ago
- ☆37Updated 6 years ago
- pyCausalFS:A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆69Updated 4 years ago
- Official implementation for NeurIPS23 paper: Causal Discovery from Subsampled Time Series with Proxy Variable☆27Updated 10 months ago
- ☆25Updated 11 months ago
- ☆29Updated 5 years ago
- Reimplementation of NOTEARS in Tensorflow☆35Updated 2 years ago
- Dynamic causal Bayesian optimisation☆35Updated last year
- ☆59Updated 4 years ago
- ☆13Updated 2 years ago
- KDD'22 Tutorial: Robust Time Series Analysis and Applications An Industrial Perspective☆32Updated last year
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆12Updated 3 years ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (Python version)☆20Updated 4 years ago
- ☆92Updated 2 years ago
- Discovering directional relations via minimum predictive information regularization☆23Updated 5 years ago
- Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…☆72Updated 4 years ago
- Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)☆27Updated 2 years ago
- Causal discovery with typed directed acyclic graphs (t-DAG). This is a ServiceNow Research project that was started at Element AI.☆13Updated last year