Papers and code of Explainable AI esp. w.r.t. Image classificiation
☆227Jun 28, 2022Updated 3 years ago
Alternatives and similar repositories for XAI
Users that are interested in XAI are comparing it to the libraries listed below
Sorting:
- ☆621Jun 28, 2023Updated 2 years ago
- LeemSaebom / Attention-Guided-CAM-Visual-Explanations-of-Vision-Transformer-Guided-by-Self-AttentionThe official code for Attention Guided CAM: Visual Explanations of Vision Transformer Guided by Self-Attention☆24Feb 7, 2024Updated 2 years ago
- Official repository of the paper "Explainable Deep Learning Methods in Medical Image Classification: A Survey", ACM Computing Surveys (CS…☆10Jan 9, 2024Updated 2 years ago
- A collection of research materials on explainable AI/ML☆1,617Dec 11, 2025Updated 2 months ago
- This repository is all about papers and tools of Explainable AI☆36Dec 20, 2019Updated 6 years ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆139Feb 19, 2021Updated 5 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆253Aug 17, 2024Updated last year
- Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.☆241Jan 30, 2026Updated last month
- Detect model's attention☆170Jul 2, 2020Updated 5 years ago
- Visualizing Deep Networks by Optimizing with Integrated Gradients (I-GOS)☆35Nov 22, 2022Updated 3 years ago
- Superpixel for CIFAR dataset☆11Sep 9, 2022Updated 3 years ago
- Local explanations with uncertainty 💐!☆42Aug 8, 2023Updated 2 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆646Jan 20, 2026Updated last month
- A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.☆10Jul 28, 2023Updated 2 years ago
- Official repository of the paper "Understanding the decisions of CNNs: an in-model approach"☆10Sep 7, 2021Updated 4 years ago
- ☆11Mar 13, 2021Updated 4 years ago
- Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch☆12Aug 30, 2024Updated last year
- Pytorch implementation of various neural network interpretability methods☆119Mar 8, 2022Updated 3 years ago
- TOpological Point Features: Node-Level Topological Representation Learning on Point Clouds☆23Jul 19, 2025Updated 7 months ago
- Model interpretability and understanding for PyTorch☆5,560Feb 24, 2026Updated last week
- 使用LSTM及股票因子数据预测未来收益，使用LRP(layer-wise relevance propagation)增强网络可解释性☆31Sep 24, 2019Updated 6 years ago
- Official repository for the AAAI-21 paper 'Explainable Models with Consistent Interpretations'☆18Apr 5, 2022Updated 3 years ago
- ☆12Mar 26, 2021Updated 4 years ago
- Fader Networks for domain adaptation on fMRI: ABIDE-II study☆12Oct 15, 2020Updated 5 years ago
- Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curv…☆16Aug 7, 2022Updated 3 years ago
- Pytorch implementation of F-CAM. Paper: "F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling".☆15Jan 21, 2023Updated 3 years ago
- This repository contains codes to explain One-Dimensional Convolutional Neural Networks (1D-CNN) using Layer-wise Relevance Propagation.☆13Aug 24, 2021Updated 4 years ago
- A curated list of awesome responsible machine learning resources.☆3,988Feb 18, 2026Updated last week
- Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are look…☆444Aug 21, 2024Updated last year
- ☆32Dec 13, 2023Updated 2 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆205May 22, 2024Updated last year
- Generate robust counterfactual explanations for machine learning models☆16Jun 8, 2023Updated 2 years ago
- Concept Relevance Propagation for Localization Models, accepted at SAIAD workshop at CVPR 2023.☆15Jan 16, 2024Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆71Jan 26, 2023Updated 3 years ago
- InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。☆259Sep 4, 2024Updated last year
- Tutorial on how to use the SHAP library to explain the feature importance with Shapley values.☆19Sep 19, 2019Updated 6 years ago
- A pytorch implemention of the Explainable AI work 'Contrastive layerwise relevance propagation (CLRP)'☆17Jun 24, 2022Updated 3 years ago
- Guidelines for the responsible use of explainable AI and machine learning.☆17Jan 30, 2023Updated 3 years ago
- Codebase for information theoretic shapley values to explain predictive uncertainty.This repo contains the code related to the paperWatso…☆22Jul 4, 2024Updated last year