Alternatives and similar repositories for awesome-causal-learning

Users that are interested in awesome-causal-learning are comparing it to the libraries listed below

• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆154Updated last year
• KColangelo / Double-ML-Continuous-Treatment
  Code for Colangelo and Lee (2025)
  ☆16Updated 11 months ago
• kochbj / Deep-Learning-for-Causal-Inference
  Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…
  ☆344Updated last year
• divyat09 / cate-estimator-selection
  Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"
  ☆14Updated last year
• anpwu / Causal4Application
  ☆26Updated 3 years ago
• causal-machine-learning-lab / mliv
  ☆30Updated 3 years ago
• claudiashi57 / dragonnet
  ☆289Updated 3 years ago
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆749Updated 3 years ago
• EddieYang211 / ebal-py
  Python implementation of Entropy Balancing for binary and continuous treatment
  ☆21Updated last month
• matthewvowels1 / Awesome-Causal-Inference
  A curated list of awesome work on causal inference, particularly in machine learning.
  ☆112Updated 4 years ago
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆104Updated 9 months ago
• edgeslab / CTL
  A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python
  ☆67Updated last year
• IntelLabs / causality-lab
  Causal discovery algorithms and tools for implementing new ones
  ☆245Updated 6 months ago
• songjiang0909 / Causal-Inference-on-Networked-Data
  Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"
  ☆20Updated 2 years ago
• d909b / drnet
  💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatm…
  ☆93Updated 2 years ago
• CausalDM / Causal-Decision-Making
  ☆42Updated 7 months ago
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆482Updated 2 years ago
• keiichishima / pcalg
  CPDAG Estimation using PC-Algorithm
  ☆96Updated 3 years ago
• cmu-phil / py-tetrad
  Makes algorithms/code in Tetrad available in Python via JPype
  ☆91Updated this week
• causal-machine-learning / kdd2021-tutorial
  EconML/CausalML KDD 2021 Tutorial
  ☆167Updated 2 years ago
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆50Updated 6 years ago
• bradyneal / realcause
  Realistic benchmark for different causal inference methods. The realism comes from fitting generative models to data with an assumed caus…
  ☆86Updated 4 years ago
• rik-helwegen / CEVAE_pytorch
  ☆45Updated 6 years ago
• Chrisejorge / Causal-Inference
  Materials Collection for Causal Inference
  ☆47Updated 2 years ago
• lushleaf / varying-coefficient-net-with-functional-tr
  [ICLR 2021] Code for: Varying Coefficient Neural Network with Functional Targeted Regularization for Estimating Continuous Treatment Effe…
  ☆93Updated 3 years ago
• felixleopoldo / benchpress
  Scalable open-source software to run, develop, and benchmark causal discovery algorithms
  ☆77Updated last week
• acmi-lab / local-causal-discovery
  Code for the paper "Local Causal Discovery for Estimating Causal Effects".
  ☆11Updated last year
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆77Updated 4 years ago
• vveitch / causality-tutorials
  Short tutorials on the use of machine learning methods for causal inference
  ☆50Updated 3 years ago
• jsyoon0823 / GANITE
  Codebase for GANITE: Estimation of Individualized Treatment Effects using GANs - ICLR 2018
  ☆66Updated 5 years ago