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Random initialisations performing above chance and how to find them


Sep 15, 2022
Frederik Benzing, Simon Schug, Robert Meier, Johannes von Oswald, Yassir Akram, Nicolas Zucchet, Laurence Aitchison, Angelika Steger


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What deep reinforcement learning tells us about human motor learning and vice-versa


Aug 26, 2022
Michele Garibbo, Casimir Ludwig, Nathan Lepora, Laurence Aitchison

* 23 pages, 5 figures 

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Out of distribution robustness with pre-trained Bayesian neural networks


Jun 24, 2022
Xi Wang, Laurence Aitchison


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Tactile Image-to-Image Disentanglement of Contact Geometry from Motion-Induced Shear


Sep 08, 2021
Anupam K. Gupta, Laurence Aitchison, Nathan F. Lepora

* 15 pages, 6 figure, under review CORL 2021 

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A fast point solver for deep nonlinear function approximators


Aug 30, 2021
Laurence Aitchison


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A variational approximate posterior for the deep Wishart process


Jul 21, 2021
Sebastian W. Ober, Laurence Aitchison

* 20 pages 

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InfoNCE is a variational autoencoder


Jul 06, 2021
Laurence Aitchison


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Data augmentation in Bayesian neural networks and the cold posterior effect


Jun 10, 2021
Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison


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BNNpriors: A library for Bayesian neural network inference with different prior distributions


May 14, 2021
Vincent Fortuin, Adrià Garriga-Alonso, Mark van der Wilk, Laurence Aitchison

* Accepted for publication at Software Impacts 

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