Popular algorithms explained in simple language with examples and links to their implementation in various programming languages and other required resources.
-
Updated
May 19, 2024
Popular algorithms explained in simple language with examples and links to their implementation in various programming languages and other required resources.
Algorithms for explaining machine learning models
moDel Agnostic Language for Exploration and eXplanation
InterpretDL: Interpretation of Deep Learning Models,基于『飞桨』的模型可解释性算法库。
Everything you need to know about Shadow DOM
Repository for the Explainable Deep One-Class Classification paper
Some information about parameters and options available in COLMAP - SfM & MVS software. https://colmap.github.io
A collection of common algorithms and data structures implemented in Java.
Awesome Explainable AI (XAI) and Interpretable ML Papers and Resources
A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).
A repository dedicated to showcasing best practices in Java and Spring through concise code snippets.
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
Meaningfully debugging model mistakes with conceptual counterfactual explanations. ICML 2022
Explaining dimensionality results using SHAP values
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
PowerShell version of explainshell.com
A list of research papers of explainable machine learning.
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang
Add a description, image, and links to the explanations topic page so that developers can more easily learn about it.
To associate your repository with the explanations topic, visit your repo's landing page and select "manage topics."