Adrian Hill
PhD student in the Machine Learning Group at TU Berlin.
Interested in in automatic differentiation, explainability and dynamical systems.
- Personal website: adrianhill.de
- GitHub profile: @adrhill
- Project spotlight
Sessions
Automatic Differentiation (AD) is the art of letting your computer work out derivatives for you. The Julia ecosystem provides many different AD tools, which can be overwhelming. This talk will give everyone the necessary information to answer two simple questions:
- As a developer, how do I make my functions differentiable?
- As a user, how do I differentiate through other people's functions?
Video: https://www.youtube.com/live/ZKt0tiG5ajw?t=19747s
ExplainableAI.jl, a comprehensive set of XAI tools for Julia, has undergone significant development since our initial presentation at JuliaCon 2022, and has since been expanded into the Julia-XAI ecosystem. This lightning talk will highlight the latest developments, including new methods, the new XAIBase.jl core interface, and new utilities for visualizing explanations of vision and language models.