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Samuel L. Smith

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

Feb 29, 2024
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

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ConvNets Match Vision Transformers at Scale

Oct 25, 2023
Samuel L. Smith, Andrew Brock, Leonard Berrada, Soham De

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Unlocking Accuracy and Fairness in Differentially Private Image Classification

Aug 21, 2023
Leonard Berrada, Soham De, Judy Hanwen Shen, Jamie Hayes, Robert Stanforth, David Stutz, Pushmeet Kohli, Samuel L. Smith, Borja Balle

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On the Universality of Linear Recurrences Followed by Nonlinear Projections

Jul 21, 2023
Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L. Smith

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Differentially Private Diffusion Models Generate Useful Synthetic Images

Feb 27, 2023
Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle

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Unlocking High-Accuracy Differentially Private Image Classification through Scale

Apr 28, 2022
Soham De, Leonard Berrada, Jamie Hayes, Samuel L. Smith, Borja Balle

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Drawing Multiple Augmentation Samples Per Image During Training Efficiently Decreases Test Error

May 27, 2021
Stanislav Fort, Andrew Brock, Razvan Pascanu, Soham De, Samuel L. Smith

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High-Performance Large-Scale Image Recognition Without Normalization

Feb 11, 2021
Andrew Brock, Soham De, Samuel L. Smith, Karen Simonyan

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On the Origin of Implicit Regularization in Stochastic Gradient Descent

Jan 28, 2021
Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De

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Characterizing signal propagation to close the performance gap in unnormalized ResNets

Jan 27, 2021
Andrew Brock, Soham De, Samuel L. Smith

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