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BEGIN:VEVENT
SUMMARY:PyHEP topical meeting - JAX ecosystem
DTSTART;VALUE=DATE-TIME:20260921T140000Z
DTEND;VALUE=DATE-TIME:20260921T153000Z
UID:174467444424
DESCRIPTION:Event URL: https://indico.cern.ch/event/1729324/\n\nSpeakers: 
 Johanna Haffner (Stealth Biotech)\n\nIntroduction to Differentiable Scient
 ific Computing in JAX + Equinox\nAutomatic differentiation is transforming
  scientific computing\, enabling gradient-based approaches to optimization
 . It powers modern artificial intelligence\, and now also transforms the w
 orld of scientific computing\, enabling end-to-end workflows bridging both
  worlds. \nThis 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 librar
 ies such as Diffrax for differential equations\, Lineax for linear solvers
 \, and Optimistix for nonlinear optimization and root-finding\, offer perf
 ormant numerics out of the box. We'll walk through key concepts and real e
 xamples showing how this ecosystem enables end-to-end differentiable scien
 tific workflows.\n\nhttps://indico.cern.ch/event/1729324/\n\nZoom: https:/
 /cern.zoom.us/j/66490871528?pwd=zTVnfnvvrNWaw2drvwHojDtKRpoqep.1
LOCATION:40/S2-A01 - Salle Anderson (CERN)
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