Patrick Kidger
Patrick is a tech lead on ML for protein optimization at Cradle.bio, and founded much of the open-source scientific JAX ecosystem. He has previously worked as an ML researcher at Google X, held a visiting appointment at Imperial College London, and received a PhD from Oxford on neural differential equations.
Sessions
This talk provides an overview of several libraries in the open-source JAX ecosystem (such as Equinox, Diffrax, Optimistix, ...) In short, we have been building an "autodifferentiable GPU-capable SciPy". These libraries offer the foundational core of tools that have made it possible for us to train neural networks (e.g. score-based diffusions for image generation), solve PDEs, and smoothly handle hybridisations of the two (e.g. fit neural ODEs to scientific data). By the end of the talk, the goal is for you to be able to walk away with a slew of new modelling tools, suitable for tackling problems both in ML and in science.