There are 1 repository under explainable topic.
📍 Interactive Studio for Explanatory Model Analysis
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
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)
A demonstration of the explainerdashboard package that that displays model quality, permutation importances, SHAP values and interactions, and individual trees for sklearn RandomForestClassifiers, etc
Explainable Machine Learning (Thessaloniki Machine Learning Meetup)
:tv: A Python library for pruning and visualizing Keras Neural Networks' structure and weights
Trustworthy LoS Prediction Based on Multi-modal Data (AIME 2023)
A 🐶🐱 explanation of generative neural nets
Python framework for explainable omics analysis
A curated list of papers on explainability and interpretability of self-driving models
CT scan machine learning models including AxialNet and HiResCAM
Final report and implementation of my systems to help groups make decisions using arguments
Code for paper https://arxiv.org/abs/1910.04256
A Explainable Artificial Intelligence tool focused in ensemble black box models, based in Item Response Theory, called eXirt.
A simple and explainable deep learning model for NLP.
A runtime monitoring tool that produces explanations as verdicts.
'Explainable' deep learning anomaly detection methods compatible with dynamic graph data