📍 Interactive Studio for Explanatory Model Analysis
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Updated
Aug 31, 2023 - R
📍 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.
A collection of algorithms of counterfactual explanations.
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
[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
Repo of the paper "On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations"
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
Counterfactual Shapley Additive Explanation: Experiments
The Pytorch implementation for "Are Data-driven Explanations Robust against Out-of-distribution Data?" (CVPR 2023)
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
A baseline genetic algorithm for the discovery of counterfactuals, implemented in Python for ease of use and heavily leveraging NumPy for speed.
XLabel: An Explainable Data Labeling Assistant
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