James Urquhart Allingham
James Urquhart Allingham
Google DeepMind
Verified email at - Homepage
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Depth uncertainty in neural networks
J Antorán*, J Allingham*, JM Hernández-Lobato
Advances in neural information processing systems 33, 10620-10634, 2020
Bayesian deep learning via subnetwork inference
E Daxberger, E Nalisnick*, JU Allingham*, J Antorán*, ...
International Conference on Machine Learning, 2510-2521, 2021
Adapting the linearised laplace model evidence for modern deep learning
J Antorán, D Janz*, JU Allingham*, E Daxberger, RR Barbano, ...
International Conference on Machine Learning, 796-821, 2022
A simple zero-shot prompt weighting technique to improve prompt ensembling in text-image models
JU Allingham*, J Ren*, MW Dusenberry, X Gu, Y Cui, D Tran, JZ Liu, ...
International Conference on Machine Learning, 547-568, 2023
Sparse MoEs meet efficient ensembles
JU Allingham, F Wenzel, ZE Mariet, B Mustafa, J Puigcerver, N Houlsby, ...
Transactions on Machine Learning Research, 2021
Deep classifiers with label noise modeling and distance awareness
V Fortuin, M Collier, F Wenzel, J Allingham, J Liu, D Tran, ...
arXiv preprint arXiv:2110.02609, 2021
Linearised laplace inference in networks with normalisation layers and the neural g-prior
J Antorán, JU Allingham, D Janz, E Daxberger, E Nalisnick, ...
Fourth Symposium on Advances in Approximate Bayesian Inference, 2022
Variational depth search in ResNets
J Antorán, JU Allingham, JM Hernández-Lobato
arXiv preprint arXiv:2002.02797, 2020
Towards anytime classification in early-exit architectures by enforcing conditional monotonicity
M Jazbec, J Allingham, D Zhang, E Nalisnick
Advances in Neural Information Processing Systems 36, 2024
Unsupervised automatic dataset repair
JU Allingham
Master’s thesis in advanced computer science, Computer Laboratory …, 2018
Addressing bias in active learning with depth uncertainty networks... or not
C Murray, JU Allingham, J Antorán, JM Hernández-Lobato
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, 59-63, 2022
Learning generative models with invariance to symmetries
JU Allingham, J Antoran, S Padhy, E Nalisnick, JM Hernández-Lobato
NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022
Model AI Assignments 2020
TW Neller, S Keeley, M Guerzhoy, W Hoenig, J Li, S Koenig, A Soni, ...
Proceedings of the AAAI conference on artificial intelligence 34 (09), 13509 …, 2020
A Product of Experts Approach to Early-Exit Ensembles
JU Allingham, E Nalisnick
Technical report, 2022
Depth Uncertainty Networks for Active Learning
C Murray, JU Allingham, J Antorán, JM Hernández-Lobato
arXiv preprint arXiv:2112.06796, 2021
A Generative Model of Symmetry Transformations
JU Allingham, BK Mlodozeniec, S Padhy, J Antorán, D Krueger, ...
arXiv preprint arXiv:2403.01946, 2024
Ensembling mixture-of-experts neural networks
R Jenatton, CR Ruiz, D Tran, JU Allingham, F Wenzel, ZE Mariet, ...
US Patent App. 17/960,780, 2023
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