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Matthew Willetts
Matthew Willetts
Research Fellow, UCL
Verified email at ucl.ac.uk - Homepage
Title
Cited by
Cited by
Year
Statistical machine learning of sleep and physical activity phenotypes from sensor data in 96,220 UK Biobank participants
M Willetts, S Hollowell, L Aslett, C Holmes, A Doherty
Scientific reports 8 (1), 7961, 2018
2162018
Explicit Regularisation in Gaussian Noise Injections
A Camuto, M Willetts, U Şimşekli, S Roberts, C Holmes
Advances in Neural Information Processing Systems (NeurIPS) 2020, 2020
622020
Improving VAEs’ Robustness to Adversarial Attack
M Willetts, A Camuto, T Rainforth, S Roberts, C Holmes
International Conference on Learning Representations (ICLR) 2021, 2021
322021
Multi-Facet Clustering Variational Autoencoders
F Falck, H Zhang, M Willetts, G Nicholson, C Yau, CC Holmes
Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021
312021
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders
A Camuto, M Willetts, S Roberts, C Holmes, T Rainforth
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
292021
I Don't Need u: Identifiable Non-Linear ICA Without Side Information
M Willetts, B Paige
arXiv preprint arXiv:2106.05238, 2021
172021
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels
M Willetts, SJ Roberts, CC Holmes
IEEE International Conference on Big Data 2020 -- Machine Learning on Big Data, 2020
17*2020
Certifiably Robust Variational Autoencoders
B Barrett, A Camuto, M Willetts, T Rainforth
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
162022
Non-determinism in tensorflow resnets
M Morin, M Willetts
arXiv preprint arXiv:2001.11396, 2020
142020
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders
M Willetts, S Roberts, C Holmes
NeurIPS 2019 Workshop on Bayesian Deep Learning, 2019
132019
A multi-resolution framework for U-Nets with applications to hierarchical VAEs
F Falck, C Williams, D Danks, G Deligiannidis, C Yau, CC Holmes, ...
Advances in Neural Information Processing Systems 35, 15529-15544, 2022
72022
Relaxed-Responsibility Hierarchical Discrete VAEs
M Willetts, X Miscouridou, S Roberts, C Holmes
NeurIPS 2021 Workshop on Bayesian Deep Learning, 2020
42020
Semi-unsupervised Learning of Human Activity using Deep Generative Models
M Willetts, A Doherty, S Roberts, C Holmes
NeurIPS 2018 ML4Health Workshop, 2018
32018
Semi-unsupervised Learning using Deep Generative Models
M Willetts, A Doherty, S Roberts, C Holmes
NeurIPS 2018 Workshop on Bayesian Deep Learning, 2018
32018
Learning Bijective Feature Maps for Linear ICA
A Camuto, M Willetts, B Paige, C Holmes, S Roberts
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
22021
Variational Autoencoders: A Harmonic Perspective
A Camuto, M Willetts
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
12022
Multiblock MEV opportunities & protections in dynamic AMMs
M Willetts, C Harrington
arXiv preprint arXiv:2404.15489, 2024
2024
Optimal Rebalancing in Dynamic AMMs
M Willetts, C Harrington
arXiv preprint arXiv:2403.18737, 2024
2024
Closed-form solutions for generic N-token AMM arbitrage
M Willetts, C Harrington
arXiv preprint arXiv:2402.06731, 2024
2024
Robustness, structure and hierarchy in deep generative models
MJF Willetts
University of Oxford, 2021
2021
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