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Andrew Y. K. Foong
Andrew Y. K. Foong
Senior Researcher, Microsoft Research
Zweryfikowany adres z microsoft.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Convolutional Conditional Neural Processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
International Conference on Learning Representations (ICLR) 2020, 2019
1332019
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
1062019
'In-Between' Uncertainty in Bayesian Neural Networks
AYK Foong, Y Li, JM Hernández-Lobato, RE Turner
Uncertainty in Deep Learning Workshop, ICML 2019, 2019
1052019
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
532020
The Gaussian Neural Process
WP Bruinsma, J Requeima, AYK Foong, J Gordon, RE Turner
Advances in Approximate Bayesian Inference (AABI) 2020, 2021
312021
Neural process family
Y Dubois, J Gordon, AY Foong
https://yanndubs.github.io/Neural-Process-Family/text/Intro.html, 2020
242020
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
212021
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
202019
Collapsed variational bounds for bayesian neural networks
M Tomczak, S Swaroop, A Foong, R Turner
Advances in Neural Information Processing Systems 34, 25412-25426, 2021
112021
Autoregressive conditional neural processes
WP Bruinsma, S Markou, J Requiema, AYK Foong, TR Andersson, ...
arXiv preprint arXiv:2303.14468, 2023
82023
Timewarp: Transferable acceleration of molecular dynamics by learning time-coarsened dynamics
L Klein, AYK Foong, TE Fjelde, B Mlodozeniec, M Brockschmidt, ...
arXiv preprint arXiv:2302.01170, 2023
82023
Evaluating approximate inference in Bayesian deep learning
AG Wilson, P Izmailov, MD Hoffman, Y Gal, Y Li, MF Pradier, S Vikram, ...
NeurIPS 2021 Competitions and Demonstrations Track, 113-124, 2022
62022
Structured Weight Priors for Convolutional Neural Networks
T Pearce, AYK Foong, A Brintrup
Uncertainty in Deep Learning Workshop, ICML 2020, 2020
52020
A note on the chernoff bound for random variables in the unit interval
AYK Foong, WP Bruinsma, DR Burt
arXiv preprint arXiv:2205.07880, 2022
42022
Fast protein backbone generation with SE (3) flow matching
J Yim, A Campbell, AYK Foong, M Gastegger, J Jiménez-Luna, S Lewis, ...
arXiv preprint arXiv:2310.05297, 2023
2023
Supplement: On the Expressiveness of Approximate Inference in Bayesian Neural Networks
AYK Foong, DR Burt, Y Li, RE Turner
Supplementary Material: Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
AYK Foong, WP Bruinsma, J Gordon, Y Dubois, J Requeima, RE Turner
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