PyHEP topical meeting - JAX ecosystem

PyHEP topical meeting - JAX ecosystem

Event URL: https://indico.cern.ch/event/1729324/ Speakers: Johanna Haffner (Stealth Biotech) Introduction to Differentiable Scientific Computing in JAX + Equinox Automatic differentiation is transforming scientific computing, enabling gradient-based approaches to optimization. It powers modern artificial intelligence, and now also transforms the world of scientific computing, enabling end-to-end workflows bridging both worlds.  This talk introduces how JAX's composable transformations and the Equinox ecosystem make this practical: Equinox provides module system built on JAX's functional paradigm with Pytorch-like syntax, while libraries such as Diffrax for differential equations, Lineax for linear solvers, and Optimistix for nonlinear optimization and root-finding, offer performant numerics out of the box. We'll walk through key concepts and real examples showing how this ecosystem enables end-to-end differentiable scientific workflows. https://indico.cern.ch/event/1729324/ Zoom: https://cern.zoom.us/j/66490871528?pwd=zTVnfnvvrNWaw2drvwHojDtKRpoqep.1

📍 40/S2-A01 - Salle Anderson (CERN)

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