📍 Interactive Studio for Explanatory Model Analysis

A Python library for Secure and Explainable Machine Learning

Explainable Machine Learning in Survival Analysis

Reading list for adversarial perspective and robustness in deep reinforcement learning.

Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images

A collection of algorithms of counterfactual explanations.

A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).

Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework

[CIKM'2023] "STExplainer: Explainable Spatio-Temporal Graph Neural Networks"

t-viSNE: Interactive Assessment and Interpretation of t-SNE Projections

Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN

Counterfactual SHAP: a framework for counterfactual feature importance

The PyTorch implementation for "DEAL: Disentangle and Localize Concept-level Explanations for VLMs" (ECCV 2024 Strong Double Blind)

Repo of the paper "On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations"

Language Model Learning a Dataset for Data-Augmented Prediction

Counterfactual Shapley Additive Explanation: Experiments

The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)

This repository contains the Business Intelligence insights generated as part of the final project challenge for the DTU Data Science course 42578: Advanced Business Analytics

XAISuite: Train machine learning models, generate explanations, and compare different explanation systems with just a simple line of code.

An R package providing functions for interpreting and distilling machine learning models