Explainable AI in Julia
The Julia-XAI ecosystem hosts Explainable AI (XAI) methods written in the Julia programming language, with a focus on post-hoc, local input-space explanations of black-box models. In simpler terms, methods that try to answer the question "Which part of the input is responsible for the model's output?".
The ecosystem is organized into several packages. As a user, you only need to install the packages that implement the methods you want to use.
As a developer, you can make use of the XAIBase.jl interface to quickly implement or prototype new methods without having to write boilerplate code.
New Users
Our recommended starting point into the Julia-XAI ecosystem is the Getting Started guide.
New Developers
If you want to implement an XAI method, take a look at the common interface defined in XAIBase.jl.
Contributing
We welcome all contributions to the Julia-XAI ecosystem! Please contact us if you want your package to be included in this organization.