📍 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"
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
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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