Autoregressive Diffusion Models
- π€ Speaker: Emiel Hoogeboom
- π Date & Time: Wednesday 30 March 2022, 11:00 - 12:30
- π Venue: Cambridge University Engineering Department, CBL Seminar room BE4-38
Abstract
Autoregressive diffusion models are a new generative model that can be seen as an autoregressive model that places a distribution over variables in random dimension order. In this talk we will discuss their relation to standard (Gaussian-based) diffusion models, and the lessons (positive and negative) we can draw from this project.
Recommended reading: the original βmodernβ diffusion paper (DDPMs) at https://arxiv.org/abs/2006.11239
Bio: Emiel is a last year PhD candidate at the University of Amsterdam under the supervision of Max Welling. Research interests include generative modelling and variational inference, for instance focusing on discrete variable extensions. He completed a BSc in Aerospace Engineering and a MSc in Artificial Intelligence. After a 3 month sabbatical he will join Google Brain in Amsterdam.
Series This talk is part of the Machine Learning Reading Group @ CUED series.
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Emiel Hoogeboom
Wednesday 30 March 2022, 11:00-12:30