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path_explain
A repository for explaining feature attributions and feature interactions in deep neural networks.treeexplainer-study
Code and documentation for experiments in the TreeExplainer paperattributionpriors
Tools for training explainable models using attribution priors.contrastiveVI
MONET
Transparent medical image AI via an image–text foundation model grounded in medical literaturecxr_covid
Code for paper "AI for radiographic COVID-19 detection selects shortcuts over signal"vit-shapley
DeepProfile
DeepProfile framework, which learns a variational autoencoder (VAE) network from a vast quantity of publicly available gene expression samples and uses the learned network to encode a low-dimensional representation (LDR) for predicting complex phenotypesIMPACT
This repository provides the dataset and code of Interpretable machine learning prediction of all-cause mortality.cxr_adv
Repository for the paper "An Adversarial Approach for the Robust Classification of Pneumonia from Chest Radiographs"AIControl.jl
Implementation of the AIControl paper in Julia 1.0shapley_algorithms
DeepSHAP
Experiments for DeepSHAP paper.MD-AD
PAUSE
Code for paper "Principled feature attribution for unsupervised gene expression analysis"coai
Cost-Aware AIexpress
Code for paper "Uncovering expression signatures of synergistic drug response in acute myeloid leukemia by explaining AI ensembles"MM-cVAE
Implementation of the moment matching contrastive VAEderm_audit
deep_attribution_priors
Reference implementation of "Learning Deep Attribution Priors Based On Prior Knowledge"deepprofile-study
Code for paper "A deep profile of gene expression across 18 human cancers"PHASE
Repository for the PHASE (PHysiologicAl Signal Embeddings) project.DIME
Code for the paper "Estimating Conditional Mutual Information for Dynamic Feature Selection"Useful_Datasets_CSE_527
ENABLAge
methylVI
A deep generative model for single-cell methylation datacl-explainability
Contrastive Corpus Attribution (COCOA)contrastiveVI-reproducibility
Repository for reproducing contrastiveVI results.Love Open Source and this site? Check out how you can help us