Skip to main content
King Abdullah University of Science and Technology
Numerical Methods for PDEs
NumPDE
Numerical Methods for PDEs

Main navigation

  • Home
  • People
    • All Profiles
    • Principal Investigators
    • Postdoctoral Fellows
    • Students
    • Former Members
  • Events
    • All Events
    • Events Calendar
  • News
  • About
  • Activities
  • Slides
  • NumPDE Workshop 2025
  • CAMWA 50
  • POEMS 2026

stochastic gradient descent

Numerical approximation of McKean-Vlasov SDEs via Stochastic Gradient Descent

Prof. Gonçalo dos Reis, School of Mathematics, University of Edinburgh

Nov 1, 15:30 - 17:00

B1 L3 R3119

stochastic gradient descent McKean-Vlasov SDEs

We propose a novel approach of numerically approximate McKean-Vlasov SDEs that avoids the usual interacting particle approximation and Propagation of Chaos results altogether.

KAUST paper wins 2020 Computational Optimization and Applications Best Paper Award

1 min read · Tue, Oct 12 2021

News

stochastic gradient descent machine learning

KAUST Professor of Computer Science Peter Richtárik and his former student Nicolas Loizou, currently a postdoctoral researcher at Mila - Quebec Artificial Intelligence Institute and soon to take up an assistant professorship position at Johns Hopkins University, recently received the 2020 Computational Optimization and Applications (COAP) Best Paper Award.

Numerical Methods for PDEs (NumPDE)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice