Andrew Y. K. Foong

According to our database1, Andrew Y. K. Foong authored at least 15 papers between 2019 and 2024.

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Bibliography

2024
Improved motif-scaffolding with SE(3) flow matching.
Trans. Mach. Learn. Res., 2024

Denoising Diffusion Probabilistic Models in Six Simple Steps.
CoRR, 2024

2023
Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Autoregressive Conditional Neural Processes.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
A Note on the Chernoff Bound for Random Variables in the Unit Interval.
CoRR, 2022

2021
The Gaussian Neural Process.
CoRR, 2021

Evaluating Approximate Inference in Bayesian Deep Learning.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Collapsed Variational Bounds for Bayesian Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

How Tight Can PAC-Bayes be in the Small Data Regime?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Structured Weight Priors for Convolutional Neural Networks.
CoRR, 2020

On the Expressiveness of Approximate Inference in Bayesian Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Convolutional Conditional Neural Processes.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks.
CoRR, 2019

'In-Between' Uncertainty in Bayesian Neural Networks.
CoRR, 2019


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