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About me

Hi, I'm Adrian! I am a PhD student in the Machine Learning Group at TU Berlin, where my research interests lie in automatic differentiation, explainability and dynamical systems. I'm a huge fan of the Julia programming language and its community.

I like to spend my free time on FOSS, image processing, board games, good coffee, and on my bike. Some day I'm going to find the time to learn Rust.

Projects

I've authored a course on Julia Programming for Machine Learning and built a bunch of packages.

For an up to date list, check out adrianhill.de/projects.

Adrian Hill's Projects

dactyl-keyboard icon dactyl-keyboard

Dactyl-ManuForm, a parameterized ergonomic keyboard translated into Python including a cadquery / Open CASCADE implementation.

datadrivendiffeq.jl icon datadrivendiffeq.jl

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

dex-lang icon dex-lang

Research language for array processing in the Haskell/ML family

diffeqflux.jl icon diffeqflux.jl

Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods

enzyme.jl icon enzyme.jl

Julia bindings for the Enzyme automatic differentiator

flux.jl icon flux.jl

Relax! Flux is the ML library that doesn't make you tensor

general icon general

The official registry of general Julia packages

highdimpde.jl icon highdimpde.jl

A Julia package that breaks down the curse of dimensionality in solving PDEs.

hyperactive icon hyperactive

A hyperparameter optimization and meta-learning toolbox for convenient and fast prototyping of machine-/deep-learning models.

innvestigate icon innvestigate

A toolbox to iNNvestigate neural networks' predictions!

jax-md icon jax-md

Differentiable, Hardware Accelerated, Molecular Dynamics

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