Yee Whye Teh

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Bio

I am interested in developing foundational methodologies for statistical machine learning.

I work on statistical machine learning, with particular focus on probabilistic learning, deep learning, meta learning, Bayesian nonparametrics, variational inference, and Monte Carlo.

Research Interests

Papers共 350 篇Author StatisticsCo-AuthorSimilar Experts

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RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Aleksandar Botev,Soham De,Samuel L Smith, Anushan Fernando, George-Cristian Muraru, Ruba Haroun,Leonard Berrada,Razvan Pascanu, Pier Giuseppe Sessa,Robert Dadashi,Léonard Hussenot,Johan Ferret,Sertan Girgin,Olivier Bachem,Alek Andreev,Kathleen Kenealy,Thomas Mesnard, Cassidy Hardin,Surya Bhupatiraju,Shreya Pathak,Laurent Sifre,Morgane Rivière,Mihir Sanjay Kale,Juliette Love, Pouya Tafti,Armand Joulin,Noah Fiedel,Evan Senter,Yutian Chen,Srivatsan Srinivasan,Guillaume Desjardins,David Budden,Arnaud Doucet,Sharad Vikram,Adam Paszke, Trevor Gale,Sebastian Borgeaud,Charlie Chen,Andy Brock, Antonia Paterson,Jenny Brennan, Meg Risdal, Raj Gundluru, Nesh Devanathan, Paul Mooney, Nilay Chauhan, Phil Culliton, Luiz Gustavo Martins, Elisa Bandy, David Huntsperger, Glenn Cameron, Arthur Zucker,Tris Warkentin, Ludovic Peran,Minh Giang,Zoubin Ghahramani,Clément Farabet,Koray Kavukcuoglu,Demis Hassabis,Raia Hadsell,Yee Whye Teh, Nando de Frietas

CoRR (2024)

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SymDiff: Equivariant Diffusion Via Stochastic Symmetrisation

Leo Zhang, Kianoosh Ashouritaklimi,Yee Whye Teh, Rob Cornish

arxiv（2024）

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Kalman Filter for Online Classification of Non-Stationary Data

Michalis Titsias,Alexandre Galashov,Amal Rannen-Triki,Razvan Pascanu,Yee Whye Teh,Jorg Bornschein

ICLR（2024）

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EvIL: Evolution Strategies for Generalisable Imitation Learning

Silvia Sapora,Gokul Swamy,Christopher Lu,Yee-Whye Teh,Jakob Foerster

ICML (2024)

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Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models

Amal Rannen-Triki,Jorg Bornschein,Razvan Pascanu,Marcus Hutter,Andras György,Alexandre Galashov,Yee Whye Teh,Michalis K. Titsias

CoRR (2024)

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The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning

Anya Sims,Cong Lu,Yee Whye Teh

CoRR (2024)

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Incorporating Unlabelled Data into Bayesian Neural Networks

Mrinank Sharma,Tom Rainforth,Yee Whye Teh,Vincent Fortuin

Trans Mach Learn Res (2024)

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Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts

Shengzhuang Chen,Jihoon Tack,Yunqiao Yang,Yee-Whye Teh,Jonathan Richard Schwarz,Ying WEI

ICML (2024)

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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Soham De,Samuel L. Smith, Anushan Fernando,Aleksandar Botev, George Cristian-Muraru,Albert Gu, Ruba Haroun,Leonard Berrada,Yutian Chen,Srivatsan Srinivasan,Guillaume Desjardins,Arnaud Doucet,David Budden,Yee Whye Teh,Razvan Pascanu,Nando De Freitas,Caglar Gulcehre

CoRR (2024)

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Papers共 350 篇Author StatisticsCo-AuthorSimilar Experts