Alternatives and similar repositories for trustworthyAI

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

• py-why / causal-learn
  Causal Discovery in Python. It also includes (conditional) independence tests and score functions.
  ☆1,427Updated last month
• FenTechSolutions / CausalDiscoveryToolbox
  Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
  ☆1,187Updated last year
• xunzheng / notears
  DAGs with NO TEARS: Continuous Optimization for Structure Learning
  ☆642Updated last year
• jvpoulos / causal-ml
  Must-read papers and resources related to causal inference and machine (deep) learning
  ☆730Updated 2 years ago
• rguo12 / awesome-causality-data
  A data index for learning causality.
  ☆473Updated last year
• IntelLabs / causality-lab
  Causal discovery algorithms and tools for implementing new ones
  ☆224Updated last month
• Renovamen / pcalg-py
  Implement PC algorithm in Python | PC 算法的 Python 实现
  ☆118Updated last year
• cmu-phil / py-tetrad
  Makes algorithms/code in Tetrad available in Python via JPype
  ☆82Updated this week
• keiichishima / pcalg
  CPDAG Estimation using PC-Algorithm
  ☆95Updated 3 years ago
• juangamella / ges
  Python implementation of the GES algorithm for causal discovery, from the 2002 paper "Optimal Structure Identification With Greedy Search…
  ☆59Updated 5 months ago
• cmu-phil / example-causal-datasets
  Example causal datasets with consistent formatting and ground truth
  ☆87Updated 3 months ago
• cdt15 / lingam
  Python package for causal discovery based on LiNGAM.
  ☆437Updated last month
• microsoft / causica
  ☆497Updated 7 months ago
• rguo12 / awesome-causality-algorithms
  An index of algorithms for learning causality with data
  ☆3,172Updated 6 months ago
• bd2kccd / py-causal
  ☆204Updated 2 years ago
• kevinsbello / dagma
  A Python 3 package for learning Bayesian Networks (DAGs) from data. Official implementation of the paper "DAGMA: Learning DAGs via M-matr…
  ☆123Updated last year
• M-Nauta / TCDF
  Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
  ☆513Updated 3 years ago
• DataCanvasIO / YLearn
  YLearn, a pun of "learn why", is a python package for causal inference
  ☆427Updated last month
• jmoss20 / notears
  Implementation of "DAGs with NO TEARS: Smooth Optimization for Structure Learning", by Zheng et al. (2018)
  ☆49Updated 6 years ago
• iancovert / Neural-GC
  Granger causality discovery for neural networks.
  ☆223Updated 4 years ago
• AliciaCurth / CATENets
  Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.
  ☆143Updated last year
• fishmoon1234 / DAG-GNN
  ☆314Updated 3 years ago
• fulifeng / Causal_Reading_Group
  We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NU…
  ☆518Updated 2 years 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…
  ☆333Updated 9 months ago
• ckassaad / causal_discovery_for_time_series
  Causal discovery for time series
  ☆100Updated 3 years ago
• clinicalml / cfrnet
  Counterfactual Regression
  ☆312Updated 2 years ago
• loeweX / AmortizedCausalDiscovery
  Code for the paper: Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data
  ☆217Updated 3 years ago
• ignavierng / golem
  On the Role of Sparsity and DAG Constraints for Learning Linear DAGs
  ☆33Updated 4 years ago
• claudiashi57 / dragonnet
  ☆276Updated 3 years ago
• divyat09 / cate-estimator-selection
  Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"
  ☆13Updated 6 months ago