Reference tables to introduce and organize evaluation methods and measures for explainable machine learning systems
☆78Mar 26, 2022Updated 4 years ago
Alternatives and similar repositories for Awesome-XAI-Evaluation
Users that are interested in Awesome-XAI-Evaluation are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- HIVE: Evaluating the Human Interpretability of Visual Explanations (ECCV 2022)☆22Jan 19, 2023Updated 3 years ago
- A Unified Approach to Evaluate and Compare Explainable AI methods☆14Jan 19, 2024Updated 2 years ago
- Counterfactual SHAP: a framework for counterfactual feature importance☆21Jul 6, 2023Updated 2 years ago
- An evaluation toolbox for machine learning explanations☆16Jan 7, 2024Updated 2 years ago
- Code/figures in Right for the Right Reasons☆57Dec 29, 2020Updated 5 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.
- PyTorch code for WWW 19 paper: On Attribution of Recurrent Neural Network Predictions via Additive Decomposition☆11Mar 18, 2021Updated 5 years ago
- Interesting resources related to XAI (Explainable Artificial Intelligence)☆855May 31, 2022Updated 4 years ago
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆255Aug 17, 2024Updated last year
- Source code for the Joint Shapley values: a measure of joint feature importance☆12Sep 14, 2021Updated 4 years ago
- Guidelines for the responsible use of explainable AI and machine learning.☆17Jan 30, 2023Updated 3 years ago
- Local explanations with uncertainty 💐!☆42Aug 8, 2023Updated 2 years ago
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆72Jan 26, 2023Updated 3 years ago
- Concealed Data Poisoning Attacks on NLP Models☆21Sep 4, 2023Updated 2 years ago
- Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI☆57Aug 17, 2022Updated 3 years ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- ☆52Aug 29, 2020Updated 5 years ago
- Code for the paper: Towards Better Understanding Attribution Methods. CVPR 2022.☆17Jun 13, 2022Updated 3 years ago
- Research model for classification and feature extraction of dermatoscopic images☆24May 22, 2023Updated 3 years ago
- Invertible Concept-based Explanation (ICE)☆19Oct 29, 2025Updated 7 months ago
- Official source code for Time is Not Enough: Time-Frequency based Explanation for Time-Series Black-Box Models☆13Dec 5, 2024Updated last year
- ☆50Mar 24, 2023Updated 3 years ago
- Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)☆82Dec 8, 2022Updated 3 years ago
- A PyTorch implementation of learning shapelets from the paper Grabocka et al., „Learning Time-Series Shapelets“.☆69Mar 3, 2022Updated 4 years ago
- ☆104Jul 6, 2023Updated 2 years ago
- Deploy to Railway using AI coding agents - Free Credits Offer • AdUse Claude Code, Codex, OpenCode, and more. Autonomous software development now has the infrastructure to match with Railway.
- ☆917Mar 19, 2023Updated 3 years ago
- Distributional Shapley: A Distributional Framework for Data Valuation☆31May 1, 2024Updated 2 years ago
- 2019년 11월 4일 제93회 점자의 날을 기념하여 점자 번역기 ‘점자로’를 공개합니다.☆31Feb 28, 2025Updated last year
- Automated Machine Learning (AutoML) for Kaggle Competition☆32Jul 6, 2023Updated 2 years ago
- A GitHub Action to run pyright☆12Dec 5, 2024Updated last year
- Detect model's attention☆176Jul 2, 2020Updated 5 years ago
- ☆11Dec 8, 2023Updated 2 years ago
- ☆44May 17, 2020Updated 6 years ago
- An Open-Source Library for the interpretability of time series classifiers☆142Nov 19, 2025Updated 6 months ago
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Code for Dataset and Benchmarks Submission, Neurips 2022☆13Aug 16, 2022Updated 3 years ago
- Supervised Local Modeling for Interpretability☆29Oct 27, 2018Updated 7 years ago
- Codebase, data and models for the Headline Grouping paper at NAACL2021☆12Oct 2, 2022Updated 3 years ago
- ☆10Mar 29, 2021Updated 5 years ago
- Codebase used in the paper "Foundational Models for Continual Learning: An Empirical Study of Latent Replay".☆29Jan 24, 2023Updated 3 years ago
- DL Backtrace is a new explainablity technique for deep learning models that works for any modality and model type.☆26May 13, 2026Updated 3 weeks ago
- List of relevant resources for machine learning from explanatory supervision☆166Jul 14, 2025Updated 10 months ago