xai

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

jphall663/awesome-machine-learning-interpretability

A curated list of awesome responsible machine learning resources.

SeldonIO/alibi

Algorithms for explaining machine learning models

oegedijk/explainerdashboard

Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.

Trusted-AI/AIX360

Interpretability and explainability of data and machine learning models

ModelOriented/DALEX

moDel Agnostic Language for Exploration and eXplanation

wangyongjie-ntu/Awesome-explainable-AI

A collection of research materials on explainable AI/ML

interpretml/DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

EthicalML/xai

XAI - An eXplainability toolbox for machine learning

lopusz/awesome-interpretable-machine-learning

pbiecek/xai_resources

Interesting resources related to XAI (Explainable Artificial Intelligence)

jphall663/interpretable_machine_learning_with_python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

deel-ai/xplique

👋 Xplique is a Neural Networks Explainability Toolbox

flyingdoog/awesome-graph-explainability-papers

Papers about explainability of GNNs

understandable-machine-intelligence-lab/Quantus

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

h2oai/mli-resources

H2O.ai Machine Learning Interpretability Resources

explainX/explainx

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

sergioburdisso/pyss3

A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)

ModelOriented/modelStudio

📍 Interactive Studio for Explanatory Model Analysis

keisen/tf-keras-vis

Neural network visualization toolkit for tf.keras

datamllab/awesome-fairness-in-ai

A curated list of awesome Fairness in AI resources

hbaniecki/adversarial-explainable-ai

💡 Adversarial attacks on explanations and how to defend them

liznerski/fcdd

Repository for the Explainable Deep One-Class Classification paper

ArrasL/LRP_for_LSTM

Layer-wise Relevance Propagation (LRP) for LSTMs.

dmlc/GNNLens2

Visualization tool for Graph Neural Networks

squaredev-io/whitebox

[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes

chr5tphr/zennit

Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.

pbiecek/ema

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models

eclique/RISE

Detect model's attention

yulongwang12/visual-attribution

Pytorch Implementation of recent visual attribution methods for model interpretability

Graph-COM/GSAT

[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.

AstraZeneca/awesome-shapley-value

Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

csinva/imodelsX

Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.

altamiracorp/awesome-xai

Awesome Explainable AI (XAI) and Interpretable ML Papers and Resources

haydengunraj/COVIDNet-CT

COVID-Net Open Source Initiative - Models and Data for COVID-19 Detection in Chest CT