Alternatives and similar repositories for bnlearn

Users that are interested in bnlearn are comparing it to the libraries listed below

• BiomedSciAI / causallib
  A Python package for modular causal inference analysis and model evaluations
  ☆785Updated 4 months ago
• cdt15 / lingam
  Python package for causal discovery based on LiNGAM.
  ☆439Updated this week
• pymc-labs / CausalPy
  A Python package for causal inference in quasi-experimental settings
  ☆1,030Updated this week
• DoubleML / doubleml-for-py
  DoubleML - Double Machine Learning in Python
  ☆640Updated this week
• AnotherSamWilson / miceforest
  Multiple Imputation with LightGBM in Python
  ☆387Updated last year
• MaxHalford / sorobn
  🧮 Bayesian networks in Python
  ☆258Updated 3 months ago
• py-why / dodiscover
  [Experimental] Global causal discovery algorithms
  ☆106Updated 3 weeks ago
• microsoft / causica
  ☆498Updated 8 months ago
• jakobrunge / tigramite
  Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at
  ☆1,510Updated 3 weeks ago
• JakeColtman / bartpy
  Bayesian Additive Regression Trees For Python
  ☆231Updated last year
• altdeep / causalML
  The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML
  ☆776Updated 2 months ago
• py-why / causaltune
  AutoML for causal inference.
  ☆228Updated 8 months ago
• cerlymarco / linear-tree
  A python library to build Model Trees with Linear Models at the leaves.
  ☆381Updated last year
• msuzen / looper
  A resource list for causality in statistics, data science and physics
  ☆265Updated last month
• erdogant / distfit
  distfit is a python library for probability density fitting.
  ☆399Updated this week
• davenza / PyBNesian
  PyBNesian is a Python package that implements Bayesian networks.
  ☆46Updated 2 weeks ago
• GAA-UAM / scikit-fda
  Functional Data Analysis Python package
  ☆332Updated last month
• WillianFuks / tfcausalimpact
  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
  ☆644Updated 7 months ago
• pymc-devs / pymc-examples
  Examples of PyMC models, including a library of Jupyter notebooks.
  ☆343Updated 3 weeks ago
• cmu-phil / py-tetrad
  Makes algorithms/code in Tetrad available in Python via JPype
  ☆83Updated 3 weeks ago
• py-why / causal-learn
  Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
  ☆1,443Updated 2 months ago
• FenTechSolutions / CausalDiscoveryToolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆1,192Updated last year
• ijmbarr / causalgraphicalmodels
  Causal Graphical Models in Python
  ☆246Updated 2 years ago
• laurencium / Causalinference
  Causal Inference in Python
  ☆572Updated 2 months ago
• scikit-learn-contrib / MAPIE
  A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
  ☆1,449Updated this week
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆628Updated last year
• dswah / pyGAM
  [CONTRIBUTORS WELCOME] Generalized Additive Models in Python
  ☆913Updated 2 weeks ago
• csinva / imodels
  Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
  ☆1,490Updated this week
• StatMixedML / XGBoostLSS
  An extension of XGBoost to probabilistic modelling
  ☆640Updated 3 weeks ago
• M-Nauta / TCDF
  Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
  ☆516Updated 3 years ago