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UID:pretalx-juliacon-2026-3H7S3S@pretalx.com
DTSTART;TZID=CET:20260812T160000
DTEND;TZID=CET:20260812T161500
DESCRIPTION:This talk presents recent advances in efficient boundary value 
 problem solving within the SciML ecosystem\, focusing on extending colloca
 tion-based and nonlinear programming formulations implemented in BoundaryV
 alueDiffEq.jl. We demonstrate how BVPs can be reformulated as structured o
 ptimization problems\, enabling seamless integration with SciML’s differ
 entiable programming stack and modern optimization tools. Building on this
  perspective\, we introduce strategies for improving performance and scala
 bility\, including structure-aware discretizations\, GPU-parallel ensemble
  solving\, and algorithmic techniques that bridge differential equation so
 lvers with optimal control and dynamical optimization pipelines. We furthe
 r show how these methods enable new application workflows\, where differen
 tial equations\, parameter estimation\, and optimal control problems are s
 olved within a unified composable framework.
DTSTAMP:20260502T103429Z
LOCATION:Room 6
SUMMARY:Efficient SciML BVP solvers: From differential equations to dynamic
  optimizations - Qingyu Qu
URL:https://pretalx.com/juliacon-2026/talk/3H7S3S/
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