ICMS-funded Workshop "New Directions for Stochastic Differential Equations and Machine Learning"

  • Neill Campbell (Organiser)
  • James Foster (Organiser)
  • Tony Shardlow (Organiser)
  • kartic Subr (Organiser)
  • Wu, Y. (Organiser)

Activity: Participating in or organising an event typesOrganiser of special symposia

Description

In recent years, the field of machine learning (ML) has seen tremendous progress, with many breakthroughs directly connected to the well-studied mathematical theory of Stochastic Differential Equations (SDEs). This increasingly fruitful relationship between SDEs and ML has produced several state-of-the-art innovations, ranging from Langevin algorithms in Bayesian learning to score-based diffusion models in computer vision.

This workshop aimed to bring the SDE and ML communities closer together and “sow the seeds” for future interdisciplinary and impactful research. The following general themes were explored:

SDE-inspired learning algorithms and architectures

Computational or learning-based algorithms for SDEs

Theoretical connections between SDEs and machine learning

Applications and areas of opportunity between disciplines
Period3 Jun 20247 Jun 2024
Event typeWorkshop
LocationEdinburgh, United KingdomShow on map