explanations
There are 71 repositories under explanations topic.
TheAlgorithms/Algorithms-Explanation
Popular algorithms explained in simple language with examples and links to their implementation in various programming languages and other required resources.
SeldonIO/alibi
Algorithms for explaining machine learning models
ModelOriented/DALEX
moDel Agnostic Language for Exploration and eXplanation
PaddlePaddle/InterpretDL
InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。
praveenpuglia/shadow-dom-in-depth
Everything you need to know about Shadow DOM
liznerski/fcdd
Repository for the Explainable Deep One-Class Classification paper
mwtarnowski/colmap-parameters
Some information about parameters and options available in COLMAP - SfM & MVS software. https://colmap.github.io
altamiracorp/awesome-xai
Awesome Explainable AI (XAI) and Interpretable ML Papers and Resources
fhvilshoj/TorchLRP
A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).
nishantc1527/Algorithms-Java
A collection of common algorithms and data structures implemented in Java.
agitrubard/java-spring-best-practices
A repository dedicated to showcasing best practices in Java and Spring through concise code snippets.
dylan-slack/Fooling-LIME-SHAP
Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
mertyg/debug-mistakes-cce
Meaningfully debugging model mistakes with conceptual counterfactual explanations. ICML 2022
wilsonjr/ClusterShapley
Explaining dimensionality results using SHAP values
akarasman/yolo-heatmaps
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
BirkhoffG/Explainable-ML-Papers
A list of research papers of explainable machine learning.
Jawz84/explainpowershell
PowerShell version of explainshell.com
dmitrykazhdan/MARLeME
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
jpmorganchase/cf-shap
Counterfactual SHAP: a framework for counterfactual feature importance
cmu-transparency/aaai-2021-tutorial
Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang
visionspacetec/Prust
PUS-C on Rust. This is the entry point for the Prust tools. List of the tools and a Wiki for them.
ojoaobrito/ExplainablePR
Code repository for the paper "A Deep Adversarial Framework for Visually Explainable Periocular Recognition" - CVPR 2021 Biometrics Workshop
devRant-Community/API-Docs
The unofficial devRant API documentation
jfc43/robust-attribution-regularization
Robust Attribution Regularization
maxidl/MMD-critic
A PyTorch based implementation of MMD-critic
mwtarnowski/graphics-and-vision-well-explained
A list of high-quality Computer Graphics & Computer Vision learning resources.
LetsUpgrade/Algorithmic-Treasure
Many time, when an interview approaches, candidates start searching for different algorithms in different programming languages for practise. This project aims to build a website which will contain the codes along with the techniques and explanations so that it can be helpful for many
jpmorganchase/cf-shap-facct22
Counterfactual Shapley Additive Explanation: Experiments
mhmgad/ExCut
Implementation of ExCut: Explainable Embedding-based Clustering over Knowledge Graphs
PrajaktaSathe/CPP
Features programs and explanations in C++. You are welcome to contribute here!
bonaert/explainable_rl
Master thesis work: explaining deep reinforcement learning policies
ModelOriented/triplot
Triplot: Instance- and data-level explanations for the groups of correlated features.
RedFox0x20/RedFox32_Old
A self learning exercise in low level system programming (OS and kernel programming) for the x86 architecture.
Villy-P/Under-the-Hood
All files included in my Youtube series: Under the Hood
Guliveer/UZ
A collection of assignments I've completed during my studies on the University of Zielona Góra since October 2023
michelecafagna26/vl-shap
[Frontiers in AI Journal] Implementation of the paper "Interpreting Vision and Language Generative Models with Semantic Visual Priors"