This repository is a curated collection of resources on Explainable Artificial Intelligence (XAI), aimed at researchers, practitioners, and anyone interested in understanding how AI models make decisions. It provides a comprehensive overview of papers, books, software tools, and articles related to XAI, serving as a valuable starting point for exploring this rapidly evolving field.

How It Works

The repository functions as a knowledge hub, aggregating and categorizing a wide range of XAI-related materials. It covers various aspects of XAI, including different explanation methods, their evaluation, ethical considerations, and applications across diverse domains. The curated nature of the content allows users to efficiently navigate the landscape of XAI research and development.

Quick Start & Requirements

• Installation: No installation is required as this is a resource repository.
• Requirements: Access to a web browser and internet connection to view the linked resources.
• Links: The README provides direct links to papers, software tools, and articles.

Highlighted Details

• Extensive collection of academic papers and preprints.
• Links to numerous software tools and libraries for XAI.
• Coverage of ethical implications and societal impact of XAI.
• Categorization of resources by type (papers, books, software, articles).

Maintenance & Community

• The repository is maintained by pbiecek.
• Further community engagement or updates are not explicitly detailed in the README.

Licensing & Compatibility

• Licensing information for the repository itself is not specified.
• Individual resources linked within the repository will have their own respective licenses.

Limitations & Caveats

This repository is a curated list of resources and does not contain executable code or provide direct XAI functionality. Users will need to access and utilize the linked external resources independently.