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Richard E. Turner
Convolutional conditional neural processes for local climate downscaling

Jan 20, 2021
Anna Vaughan, Will Tebbutt, J. Scott Hosking, Richard E. Turner

* 26 pages, 12 figures 
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The Gaussian Neural Process

Jan 10, 2021
Wessel P. Bruinsma, James Requeima, Andrew Y. K. Foong, Jonathan Gordon, Richard E. Turner

* 34 pages; includes supplementary material; to appear in AABI 2020 
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Generalized Variational Continual Learning

Nov 24, 2020
Noel Loo, Siddharth Swaroop, Richard E. Turner


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Sparse Gaussian Process Variational Autoencoders

Oct 23, 2020
Matthew Ashman, Jonathan So, Will Tebbutt, Vincent Fortuin, Michael Pearce, Richard E. Turner

* 19 pages, 6 figures 
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Diagnostic Questions:The NeurIPS 2020 Education Challenge

Aug 03, 2020
Zichao Wang, Angus Lamb, Evgeny Saveliev, Pashmina Cameron, Yordan Zaykov, José Miguel Hernández-Lobato, Richard E. Turner, Richard G. Baraniuk, Craig Barton, Simon Peyton Jones, Simon Woodhead, Cheng Zhang

* 28 pages, 6 figures, NeurIPS 2020 Competition Track 
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Interpreting Spatially Infinite Generative Models

Jul 24, 2020
Chaochao Lu, Richard E. Turner, Yingzhen Li, Nate Kushman

* ICML 2020 workshop on Human Interpretability in Machine Learning (WHI 2020) 
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Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes

Jul 02, 2020
Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner


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Continual Deep Learning by Functional Regularisation of Memorable Past

Apr 29, 2020
Pingbo Pan, Siddharth Swaroop, Alexander Immer, Runa Eschenhagen, Richard E. Turner, Mohammad Emtiyaz Khan


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TaskNorm: Rethinking Batch Normalization for Meta-Learning

Mar 06, 2020
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner


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Semi-supervised Bootstrapping of Dialogue State Trackers for Task Oriented Modelling

Nov 26, 2019
Bo-Hsiang Tseng, Marek Rei, Paweł Budzianowski, Richard E. Turner, Bill Byrne, Anna Korhonen

* This article is published at EMNLP-IJCNLP 2019 
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Differentially Private Federated Variational Inference

Nov 24, 2019
Mrinank Sharma, Michael Hutchinson, Siddharth Swaroop, Antti Honkela, Richard E. Turner

* Privacy in Machine Learning Workshop (PriML 2019) at the 33rd Conference in Neural Information and Processing Systems (NeurIPS) 
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Continual Learning with Adaptive Weights (CLAW)

Nov 21, 2019
Tameem Adel, Han Zhao, Richard E. Turner


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Scalable Exact Inference in Multi-Output Gaussian Processes

Nov 14, 2019
Wessel P. Bruinsma, Eric Perim, Will Tebbutt, J. Scott Hosking, Arno Solin, Richard E. Turner

* 19 pages, 9 figures, includes appendix 
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Convolutional Conditional Neural Processes

Oct 29, 2019
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner


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Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations

Sep 05, 2019
Jan Stühmer, Richard E. Turner, Sebastian Nowozin


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Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks

Sep 02, 2019
Andrew Y. K. Foong, David R. Burt, Yingzhen Li, Richard E. Turner


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'In-Between' Uncertainty in Bayesian Neural Networks

Jun 27, 2019
Andrew Y. K. Foong, Yingzhen Li, José Miguel Hernández-Lobato, Richard E. Turner

* Presented at the ICML 2019 Workshop on Uncertainty and Robustness in Deep Learning 
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Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes

Jun 18, 2019
James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner


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Practical Deep Learning with Bayesian Principles

Jun 06, 2019
Kazuki Osawa, Siddharth Swaroop, Anirudh Jain, Runa Eschenhagen, Richard E. Turner, Rio Yokota, Mohammad Emtiyaz Khan

* Under review 
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Fast computation of loudness using a deep neural network

May 24, 2019
Josef Schlittenlacher, Richard E. Turner, Brian C. J. Moore


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Improving and Understanding Variational Continual Learning

May 06, 2019
Siddharth Swaroop, Cuong V. Nguyen, Thang D. Bui, Richard E. Turner


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Partitioned Variational Inference: A unified framework encompassing federated and continual learning

Nov 27, 2018
Thang D. Bui, Cuong V. Nguyen, Siddharth Swaroop, Richard E. Turner


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Infinite-Horizon Gaussian Processes

Nov 15, 2018
Arno Solin, James Hensman, Richard E. Turner

* To appear in Advances in Neural Information Processing Systems (NIPS 2018) 
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Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning

Oct 15, 2018
Aapo Hyvarinen, Hiroaki Sasaki, Richard E. Turner


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Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks

Oct 09, 2018
Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt

* 9 pages, 5 figures 
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Gaussian Process Behaviour in Wide Deep Neural Networks

Aug 16, 2018
Alexander G. de G. Matthews, Mark Rowland, Jiri Hron, Richard E. Turner, Zoubin Ghahramani

* This work substantially extends the work of Matthews et al. (2018) published at the International Conference on Learning Representations (ICLR) 2018 
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Structured Evolution with Compact Architectures for Scalable Policy Optimization

Jun 12, 2018
Krzysztof Choromanski, Mark Rowland, Vikas Sindhwani, Richard E. Turner, Adrian Weller


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Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning

May 31, 2018
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner


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