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awesome-jax's Introduction

Hi there ๐Ÿ‘‹ Iโ€™m Phillip, a PhD student in the Qualcomm-UvA lab (QUVA) at the University of Amsterdam supervised by Efstratios Gavves and Taco Cohen. My research focuses on the intersection of causality and machine learning ๐Ÿค–, but I am also interested in generative modeling ๐ŸŒ€, reinforcement learning ๐Ÿ•น, AI4Science ๐Ÿงช, and natural language processing ๐Ÿ’ฌ. Besides that, I like teaching ๐Ÿ‘จโ€๐Ÿซ. A short guide of my main repositories:

Teaching/Education

  • uvadlc_notebooks: Jupyter notebook tutorials for the Deep Learning course at UvA. They cover basic deep learning topics such as initialization and optimization, to more complex topics including Normalizing Flows, Vision Transformers and Meta Learning. All notebooks executed can be viewed on our RTD website, and are integrated in PyTorch Lightning's documentation.
  • UvA_summaries: A collection of summaries that I wrote during my Master studies of Artificial Intelligence at the University of Amsterdam (2018-2020). Topics cover courses including Machine Learning, Reinforcement Learning, and many more.
  • jax_trainer: A small library for providing a Lightning-like API for JAX with Flax. A template research repository based on jax_trainer is shown here.

Research

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