Alternatives and similar repositories for OmniXAI:

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

• interpretml / DiCE
  Generate Diverse Counterfactual Explanations for any machine learning model.
  ☆1,401Updated 5 months ago
• SeldonIO / alibi
  Algorithms for explaining machine learning models
  ☆2,495Updated last month
• csinva / imodels
  Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
  ☆1,449Updated 2 months ago
• wangyongjie-ntu / Awesome-explainable-AI
  A collection of research materials on explainable AI/ML
  ☆1,490Updated last month
• AI4LIFE-GROUP / OpenXAI
  OpenXAI : Towards a Transparent Evaluation of Model Explanations
  ☆245Updated 8 months ago
• explainX / explainx
  Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are look…
  ☆430Updated 8 months ago
• EthicalML / xai
  XAI - An eXplainability toolbox for machine learning
  ☆1,166Updated 3 years ago
• SeldonIO / alibi-detect
  Algorithms for outlier, adversarial and drift detection
  ☆2,354Updated 2 weeks ago
• eli5-org / eli5
  A library for debugging/inspecting machine learning classifiers and explaining their predictions
  ☆290Updated 2 weeks ago
• deel-ai / xplique
  👋 Xplique is a Neural Networks Explainability Toolbox
  ☆688Updated 6 months ago
• scikit-learn-contrib / MAPIE
  A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
  ☆1,374Updated this week
• linkedin / FastTreeSHAP
  Fast SHAP value computation for interpreting tree-based models
  ☆539Updated last year
• carla-recourse / CARLA
  CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
  ☆288Updated last year
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆576Updated 10 months ago
• IFCA-Advanced-Computing / frouros
  Frouros: an open-source Python library for drift detection in machine learning systems.
  ☆215Updated 3 months ago
• PAIR-code / what-if-tool
  Source code/webpage/demos for the What-If Tool
  ☆946Updated 7 months ago
• understandable-machine-intelligence-lab / Quantus
  Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
  ☆598Updated 2 months ago
• BiomedSciAI / causallib
  A Python package for modular causal inference analysis and model evaluations
  ☆769Updated last month
• pbiecek / xai_resources
  Interesting resources related to XAI (Explainable Artificial Intelligence)
  ☆827Updated 2 years ago
• manujosephv / pytorch_tabular
  A standard framework for modelling Deep Learning Models for tabular data
  ☆1,492Updated this week
• Trusted-AI / AIX360
  Interpretability and explainability of data and machine learning models
  ☆1,683Updated 2 months ago
• sdv-dev / SDGym
  Benchmarking synthetic data generation methods.
  ☆273Updated last week
• interpretml / interpret-community
  Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…
  ☆428Updated 2 months ago
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆268Updated last week
• cdpierse / transformers-interpret
  Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.
  ☆1,337Updated last year
• kathrinse / be_great
  A novel approach for synthesizing tabular data using pretrained large language models
  ☆309Updated 6 months ago
• CalculatedContent / WeightWatcher
  The WeightWatcher tool for predicting the accuracy of Deep Neural Networks
  ☆1,583Updated 7 months ago
• kathrinse / TabSurvey
  Experiments on Tabular Data Models
  ☆277Updated last year
• microsoft / causica
  ☆478Updated 4 months ago
• TorchDrift / TorchDrift
  Drift Detection for your PyTorch Models
  ☆316Updated 2 years ago