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Sander Dieleman

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Reduce, Reuse, Recycle: Compositional Generation with Energy-Based Diffusion Models and MCMC

Feb 22, 2023
Yilun Du, Conor Durkan, Robin Strudel, Joshua B. Tenenbaum, Sander Dieleman, Rob Fergus, Jascha Sohl-Dickstein, Arnaud Doucet, Will Grathwohl

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Continuous diffusion for categorical data

Dec 15, 2022
Sander Dieleman, Laurent Sartran, Arman Roshannai, Nikolay Savinov, Yaroslav Ganin, Pierre H. Richemond, Arnaud Doucet, Robin Strudel, Chris Dyer, Conor Durkan, Curtis Hawthorne, Rémi Leblond, Will Grathwohl, Jonas Adler

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Self-conditioned Embedding Diffusion for Text Generation

Nov 08, 2022
Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, Rémi Leblond

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Categorical SDEs with Simplex Diffusion

Oct 26, 2022
Pierre H. Richemond, Sander Dieleman, Arnaud Doucet

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General-purpose, long-context autoregressive modeling with Perceiver AR

Feb 15, 2022
Curtis Hawthorne, Andrew Jaegle, Cătălina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse Engel

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Towards Learning Universal Audio Representations

Dec 01, 2021
Luyu Wang, Pauline Luc, Yan Wu, Adria Recasens, Lucas Smaira, Andrew Brock, Andrew Jaegle, Jean-Baptiste Alayrac, Sander Dieleman, Joao Carreira, Aaron van den Oord

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Variable-rate discrete representation learning

Mar 10, 2021
Sander Dieleman, Charlie Nash, Jesse Engel, Karen Simonyan

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