explainable
There are 21 repositories under explainable topic.
ModelOriented/modelStudio
📍 Interactive Studio for Explanatory Model Analysis
AstraZeneca/awesome-shapley-value
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
MI2DataLab/survshap
SurvSHAP(t): Time-dependent explanations of machine learning survival models
rehmanzafar/xai-iml-sota
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
lethaiq/GRACE_KDD20
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model’s Prediction. Thai Le, Suhang Wang, Dongwon Lee. 26th ACM SIGKDD Int’l Conf. on Knowledge Discovery and Data Mining (KDD)
oegedijk/explainingtitanic
A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
EPSOFT/explainable
explainable
iamollas/Explainable_ML_Meetup
Explainable Machine Learning (Thessaloniki Machine Learning Meetup)
yuvalailer/nnplot
:tv: A Python library for pruning and visualizing Keras Neural Networks' structure and weights
MI2DataLab/xlungs-trustworthy-los-prediction
Trustworthy LoS Prediction Based on Multi-modal Data (AIME 2023)
breimanntools/xomics
Python framework for explainable omics analysis
EloiZ/awesome_explainable_driving
A curated list of papers on explainability and interpretability of self-driving models
wodeni/image-synthesis-explained
A 🐶🐱 explanation of generative neural nets
rachellea/explainable-ct-ai
CT scan machine learning models including AxialNet and HiResCAM
feeney92/Group_Decision_Making_System
Final report and implementation of my systems to help groups make decisions using arguments
roye10/gshap
This module extends the kernel SHAP method (as introduced by Lundberg and Lee (2017)) which is local in nature, to a method that computes global SHAP values.
chirag126/generative-attribution-methods
Code for paper https://arxiv.org/abs/1910.04256
johnaaron-git/masters-thesis
'Explainable' deep learning anomaly detection methods compatible with dynamic graph data
josesousaribeiro/eXirt
A Explainable Artificial Intelligence tool focused in ensemble black box models, based in Item Response Theory, called eXirt.
KieranLitschel/XSWEM
A simple and explainable deep learning model for NLP.
runtime-monitoring/whymon
A runtime monitoring tool that produces explanations as verdicts