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International Conference on Scientific Computing and Machine Learning 2026
University of Bath, UK, September 14 - 18, 2026.

Supported by UK/Japan Research Programmes: Maths4DL EPSRC Programme on the Mathematics of Deep Learning, JST CREST of Operator Learning Based on Geometric Classical Field Theory and Infinite Dimensional Data Science and JST ASPIRE of Deep scientific computing: integration of physical structure and deep learning through mathematical science.
International Conference on Scientific Computing and Machine Learning 2026
University of Bath, UK, September 14 - 18, 2026.

Supported by UK/Japan Research Programmes: Maths4DL EPSRC Programme on the Mathematics of Deep Learning, JST CREST of Operator Learning Based on Geometric Classical Field Theory and Infinite Dimensional Data Science and JST ASPIRE of Deep scientific computing: integration of physical structure and deep learning through mathematical science.
International Conference on Scientific Computing and Machine Learning 2026
University of Bath, UK, September 14 - 18, 2026.

Supported by UK/Japan Research Programmes: Maths4DL EPSRC Programme on the Mathematics of Deep Learning, JST CREST of Operator Learning Based on Geometric Classical Field Theory and Infinite Dimensional Data Science and JST ASPIRE of Deep scientific computing: integration of physical structure and deep learning through mathematical science.
International Conference on Scientific Computing and Machine Learning 2026
University of Bath, UK, September 14 - 18, 2026.

Supported by UK/Japan Research Programmes: Maths4DL EPSRC Programme on the Mathematics of Deep Learning, JST CREST of Operator Learning Based on Geometric Classical Field Theory and Infinite Dimensional Data Science and JST ASPIRE of Deep scientific computing: integration of physical structure and deep learning through mathematical science.

Welcome

In recent years, machine learning methods for scientific computing have attracted much attention. Many methods are a combination of machine learning and/or theories of physics and/or computational mathematics.

This conference aims to showcase the latest research in these areas, which have been fragmented while pursuing research in the same direction, to bridge the gap between them, and to promote collaboration.

Topics will include, but not limited to

  • ML for inverse problems
  • ML for differential equations
  • Operator learning
  • Neural ODEs and reconstruction of dynamics
  • Generative modelling
  • Geometric deep learning
  • Applications to:
    • Geo and environmental sciences (including weather and climate forecasting)
    • Medical imaging
    • Control theory
    • electromagnetics
    • drug discovery

Please contact the organizers at yaguchi (at) pearl.kobe-u.ac.jp or scml26-committee (at) geom.jp with any questions.

Conference venue

University of Bath

Claverton Down, Bath BA2 7AY, UK

Accommodation

TBA

Call for contributed talks

TBA

Important Dates

  • Contributed talks submissions due: TBA
  • Notification to authors: TBA

Tutorial/keynote/invited speakers

The current confirmed tutorial/keynote/invited speakers are
  • Gabriele Steidl (TU Berlin)
  • Elena Celledoni (NTNU)
  • Tom Pock (TU Graz)
  • Caroline Moosmuller (University of North Carolina)
  • Sofya Maslovskaya (Padeborn University)
  • Katarzyna Michalowska (SINTEF)
  • Leon Bungert (University of Würzburg)
  • Yeonjong Shin (NC State University)
  • Noboru Isobe (RIKEN)

Registration

Registration is required for you to participate in the conference. In particular, to present your work, at least one of the authors should make a registration.

A system for registration will be available soon.

Registration fee

TBA

Organizers

  • Christopher J. Budd OBE (University of Bath)
  • Matthias J. Ehrhardt (University of Bath)
  • Mizuka Komatsu (Kobe University)
  • Yury Korolev (University of Bath)
  • Davide Murai (University of Cambridge)
  • Chaoyu Liu (University of Cambridge)
  • Amy Lunt (University of Bath)
  • Takaharu Yaguchi (Kobe University)
  • Baige Xu (Kobe University)

This conference is supported by EPSRC Programme Grant Maths4DL on "the Mathematics of Deep Learning," JST CREST Prediction Mathematical Foundation "Operator Learning Based on Geometric Classical Field Theory and Infinite Dimensional Data Science," and by JST ASPIRE "Deep scientific computing: integration of physical structure and deep learning through mathematical science."

Notation based on the Specified Commercial Transaction Act