The Computing Division Technical Meetings are a platform for

  • presenting Pinboard papers under review for journal or conference publication,
  • inviting speakers who are current or prospective UKAEA collaborators at external organisations,
  • presenting work done in PhD projects funded by or co-supervised by UKAEA,
  • presenting work done during summer placements or other secondments to UKAEA.

 

If you would like to invite a speaker on a topic that would be of interest to one or more Units within the Computing Division, but is not currently collaborating on a UKAEA project, please consider nominating them for a Computing Division Cross-Disciplinary Seminar.

These meetings are normally recorded. Recordings of past meetings can be found here:

CD Technical Meetings Archive on UKAEA Sharepoint

CD Technical Meeting (ML6): GPs for Physics-informed Manifold Learning and EFIT Shape Inference from MAST images

→ Europe/London
Cyd Cowley (digiLab), Aravinda Perera (Plasma Simulation)
Description
Machine Learning, Uncertainty Quantification and Data Science 

 

Challenges in Physics-Informed Manifold Learning for Gaussian Processes: This talk introduces the motivation for Physics-Informed Gaussian Processes (GPs), focusing on how constraining manifold learning with differential equations impacts GP performance. Key concepts include Gaussian Processes, nonlinear dimensionality reduction (including VAEs), and Physics-Informed Neural Networks (PINNs).

Computer Vision for EFIT Shape Inference in MAST: This project explores the use of camera data from the MAST tokamak to infer plasma shape parameters, with the goal of assessing its potential as a complementary diagnostic. A computer vision pipeline is developed to extract plasma boundary features from experimental video frames, which are then used to predict equilibrium shape parameters using a Gaussian process model. The approach demonstrates the feasibility of deriving meaningful shape information from visual data alone, offering a novel, non-invasive route for plasma diagnostics.

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