Stebėti
Matthew Willetts
Matthew Willetts
Research Fellow, UCL
Patvirtintas el. paštas ucl.ac.uk - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
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
2012018
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
562020
Improving VAEs’ Robustness to Adversarial Attack
M Willetts, A Camuto, T Rainforth, S Roberts, C Holmes
International Conference on Learning Representations (ICLR) 2021, 2021
302021
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
272021
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
252021
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
142022
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
112019
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
62022
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
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
We don’t need AI to pass the Turing Test to be helpful in healthcare
W Warr, M Willetts, C Holmes
the BMJ opinion, 2019
2019
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Straipsniai 1–19