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Physics-Informed Generative Networks
You can also join remotely.
Generative models, such as GANs and diffusion models, have yet to fully incorporate the nuances of physical information. In this presentation, we address this oversight from two distinct yet opposite angles. First, we’ll showcase how incorporating physical models into GANs can enhance their control and output quality. Conversely, we’ll explore how advanced large scale diffusion models, especially Stable Diffusion, can be harnessed to discern physical attributes from natural images.
Bio:
Dr Fabio Pizzati is a postdoctoral researcher in the Torr Vision Group at the University of Oxford, working with Prof. Phil Torr. He is currently working on large scale diffusion models for image generation, and continual learning.
Date:
6 December 2023, 13:00
Venue:
Wolfson College, Linton Road OX2 6UD
Venue Details:
Seminar Room 2 - The Academic Wing
Speaker:
Dr Fabio Pizzati (University of Oxford)
Organising department:
Wolfson College
Organiser:
Dr. Yi Yin (Wolfson College, University of Oxford)
Organiser contact email address:
yi.yin@wrh.ox.ac.uk
Part of:
Oxford Cross-Disciplinary Machine Learning (OxfordXML) Research Cluster Seminar Series
Booking required?:
Not required
Cost:
Free (cake, tea and coffee provided)
Audience:
Public
Editor:
Yi Yin
