causal-discovery

There are 99 repositories under causal-discovery topic.

  • Rath

    Kanaries/Rath

    Next generation of automated data exploratory analysis and visualization platform.

    Language:TypeScript4k44139299

  • pgmpy/pgmpy

    Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.

    Language:Python2.6k74872693

  • FenTechSolutions/CausalDiscoveryToolbox

    Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.

    Language:Python1.1k37143199

  • py-why/causal-learn

    Causal Discovery in Python. It also includes (conditional) independence tests and score functions.

    Language:Python1k1596172

  • jvpoulos/causal-ml

    Must-read papers and resources related to causal inference and machine (deep) learning

    625270116

  • DataCanvasIO/YLearn

    YLearn, a pun of "learn why", is a python package for causal inference

    Language:Python382113175

  • cdt15/lingam

    Python package for causal discovery based on LiNGAM.

    Language:Python347114352

  • msuzen/looper

    A resource list for causality in statistics, data science and physics

    243123632

  • loeweX/AmortizedCausalDiscovery

    Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data

    Language:Python1957841

  • IntelLabs/causality-lab

    Causal discovery algorithms and tools for implementing new ones

    Language:Jupyter Notebook14310218

  • majianthu/pycopent

    Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python

    Language:Python1393029

  • Wuyxin/DIR-GNN

    Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

    Language:Python11451514

  • kevinsbello/dagma

    A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization"

    Language:Python793518

  • phlippe/ENCO

    Official repository of the paper "Efficient Neural Causal Discovery without Acyclicity Constraints"

    Language:Python763415

  • felixleopoldo/benchpress

    A Snakemake workflow to run and benchmark structure learning (a.k.a. causal discovery) algorithms for probabilistic graphical models.

    Language:Python6154416

  • larslorch/avici

    Amortized Inference for Causal Structure Learning, NeurIPS 2022

    Language:Python48135

  • lazaratan/dyn-gfn

    DynGFN: Bayesian Dynamic Causal Discovery using Generative Flow Networks

    Language:Python462211

  • chritoth/active-bayesian-causal-inference

    Active Bayesian Causal Inference (Neurips'22)

    Language:Python45315

  • majianthu/copent

    R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test

    Language:R38209

  • majianthu/transferentropy

    Code for the paper "Estimating Transfer Entropy via Copula Entropy"

    Language:R370013

  • polixir/causal-mbrl

    Toolkit of Causal Model-based Reinforcement Learning.

    Language:Python32311

  • weirayao/leap

    LEAP is a tool for discovering latent temporal causal relations with gradient-based neural network.

    Language:Jupyter Notebook32216

  • causy-dev/causy

    Causal discovery made easy.

    Language:Python203140

  • WellyZhang/ACRE

    ACRE: Abstract Causal REasoning Beyond Covariation

    Language:Python18201

  • Amber-Yes-We-Code/leap

    LEAP is a novel tool for discovering latent temporal causal relations.

    Language:Jupyter Notebook17102

  • CausalInferenceLab/causal-inference-practice

    가짜연구소 <인과추론과 실무> 프로젝트

    17030

  • Scriddie/Varsortability

    Implementations of var-sortability, sortnregress, and chain-orientation as presented in the article "Beware of the Simulated DAG": https://arxiv.org/abs/2102.13647.

    Language:Python14402

  • ErdunGAO/FedDAG

    [TMLR23] FedDAG: Federated DAG Structure Learning

    Language:Python13103

  • rpatrik96/nl-causal-representations

    This is the code for the paper Jacobian-based Causal Discovery with Nonlinear ICA, demonstrating how identifiable representations (particularly, with Nonlinear ICA) can be used to extract the causal graph from an underlying structural equation model (SEM).

    Language:Python13321

  • YangLiu9208/CMCIR

    [IEEE T-PAMI 2023] Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering

    Language:Python13536

  • lmz123321/proxy_causal_discovery

    Official implementation for NeurIPS23 paper: Causal Discovery from Subsampled Time Series with Proxy Variable

    Language:Python12100

  • ServiceNow/typed-dag

    Causal discovery with typed directed acyclic graphs (t-DAG). This is a ServiceNow Research project that was started at Element AI.

    Language:Python12605

  • shlizee/TimeAwarePC

    A python package for finding causal functional connectivity from neural time series observations.

    Language:Python12402

  • liuff19/ReScore

    [ICLR 2023] ReScore: Boosting Causal Discovery via Adaptive Sample Reweighting

    Language:Python10100

  • UzmaHasan/KCRL

    Causal Discovery with Prior Knowledge

    Language:Python10200

  • microsoft/ML4C

    [SDM'23] ML4C: Seeing Causality Through Latent Vicinity

    Language:Python9402