Papers and code of Explainable AI esp. w.r.t. Image classificiation
☆226Jun 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. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- 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
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆851May 31, 2022Updated 3 years ago
- A collection of research materials on explainable AI/ML☆1,627Mar 7, 2026Updated last month
- Code for "Interpretable Image Recognition with Hierarchical Prototypes"☆19Nov 1, 2019Updated 6 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆254Aug 17, 2024Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- This repository is all about papers and tools of Explainable AI☆36Dec 20, 2019Updated 6 years ago
- Visualizing Deep Networks by Optimizing with Integrated Gradients (I-GOS)☆35Nov 22, 2022Updated 3 years ago
- Detect model's attention☆174Jul 2, 2020Updated 5 years ago
- A PyTorch 1.6 implementation of Layer-Wise Relevance Propagation (LRP).☆138Feb 19, 2021Updated 5 years ago
- Local explanations with uncertainty 💐!☆42Aug 8, 2023Updated 2 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Dec 8, 2022Updated 3 years ago
- PyTorch implementation of Interpretable Explanations of Black Boxes by Meaningful Perturbation☆337Nov 30, 2021Updated 4 years ago
- Generate robust counterfactual explanations for machine learning models☆17Jun 8, 2023Updated 2 years ago
- Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations☆657Mar 9, 2026Updated last month
- Serverless GPU API endpoints on Runpod - Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Implementation of the paper titled: "FACE: Feasible and actionable counterfactual recourse" by Rafael et. at. - https://arxiv.org/pdf/190…☆14Dec 12, 2020Updated 5 years ago
- ☆215Apr 3, 2021Updated 5 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Apr 23, 2022Updated 3 years ago
- A Python library for pruning and visualizing Keras Neural Networks' structure and weights☆10Dec 24, 2019Updated 6 years ago
- ☆15Jan 2, 2023Updated 3 years ago
- Fader Networks for domain adaptation on fMRI: ABIDE-II study☆12Oct 15, 2020Updated 5 years ago
- ☆16Aug 3, 2022Updated 3 years ago
- TOpological Point Features: Node-Level Topological Representation Learning on Point Clouds☆23Jul 19, 2025Updated 8 months ago
- code release for the paper "On Completeness-aware Concept-Based Explanations in Deep Neural Networks"☆54Mar 25, 2022Updated 4 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Official PyTorch code for the CVPR 2022 paper - Consistent Explanations by Contrastive Learning☆18Sep 11, 2022Updated 3 years ago
- Here I gather promising research directions to make DNNs interpretable☆17Apr 11, 2024Updated 2 years ago
- Explaining Deep Convolutional Neural Networks via Unsupervised Visual-Semantic Filter Attention (CVPR 2022)☆20Mar 31, 2022Updated 4 years ago
- Explain Neural Networks using Layer-Wise Relevance Propagation and evaluate the explanations using Pixel-Flipping and Area Under the Curv…☆17Aug 7, 2022Updated 3 years ago
- Model interpretability and understanding for PyTorch☆5,600Updated this week
- ☆13Jul 23, 2020Updated 5 years ago
- XAI - An eXplainability toolbox for machine learning☆1,232Nov 29, 2025Updated 4 months ago
- Official repository of the paper "Understanding the decisions of CNNs: an in-model approach"☆10Sep 7, 2021Updated 4 years ago
- InterpretDL: Interpretation of Deep Learning Models，基于『飞桨』的模型可解释性算法库。☆261Sep 4, 2024Updated last year
- Serverless GPU API endpoints on Runpod - Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- Interpretable Explanations of Black Boxes by Meaningful Perturbation Pytorch☆12Aug 30, 2024Updated last year
- Codebase for information theoretic shapley values to explain predictive uncertainty.This repo contains the code related to the paperWatso…☆22Jul 4, 2024Updated last year
- Integrated Grad-CAM (submitted to ICASSP2021 conference)☆19Feb 8, 2021Updated 5 years ago
- ☆16Feb 11, 2021Updated 5 years ago
- Attribution (or visual explanation) methods for understanding video classification networks. Demo codes for WACV2021 paper: Towards Visua…☆21Oct 3, 2023Updated 2 years ago
- BrainProp: How the brain can implement reward-based error backpropagation☆17Dec 8, 2022Updated 3 years ago
- [ICCV 2023] The official PyTorch implementation of the Iterated Integrated Attributions (IIA) method.☆14Mar 13, 2026Updated last month