Andrew Y. K. Foong
Title
Cited by
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Year
Convolutional Conditional Neural Processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
International Conference on Learning Representations (ICLR) 2020, 2019
372019
'In-Between' Uncertainty in Bayesian Neural Networks
AYK Foong, Y Li, JM HernŠndez-Lobato, RE Turner
Uncertainty in Deep Learning Workshop, ICML 2019, 2019
372019
On the Expressiveness of Approximate Inference in Bayesian Neural Networks
AYK Foong, DR Burt, Y Li, RE Turner
Neural Information Processing Systems (NeurIPS) 2020, 2019
182019
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
AYK Foong, WP Bruinsma, J Gordon, Y Dubois, J Requeima, RE Turner
Neural Information Processing Systems (NeurIPS) 2020, 2020
122020
Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks
AYK Foong, DR Burt, Y Li, RE Turner
Bayesian Deep Learning Workshop, NeurIPS 2019, 2019
122019
The Gaussian Neural Process
WP Bruinsma, J Requeima, AYK Foong, J Gordon, RE Turner
Advances in Approximate Bayesian Inference (AABI) 2020, 2021
32021
Structured Weight Priors for Convolutional Neural Networks
T Pearce, AYK Foong, A Brintrup
Uncertainty in Deep Learning Workshop, ICML 2020, 2020
12020
How Tight Can PAC-Bayes be in the Small Data Regime?
AYK Foong, WP Bruinsma, DR Burt, RE Turner
Neural Information Processing Systems (NeurIPS) 2021, 2021
2021
Evaluating Approximate Inference in Bayesian Deep Learning
AG Wilson, P Izmailov, MD Hoffman, Y Gal, Y Li, MF Pradier, S Vikram, ...
2021
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