受强制性开放获取政策约束的文章 - James Urquhart Allingham了解详情
可在其他位置公开访问的文章：7 篇
Depth uncertainty in neural networks
J Antorán*, J Allingham*, JM Hernández-Lobato
Advances in neural information processing systems 33, 10620-10634, 2020
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
Bayesian deep learning via subnetwork inference
E Daxberger, E Nalisnick*, JU Allingham*, J Antorán*, ...
International Conference on Machine Learning, 2510-2521, 2021
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
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
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
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
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
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
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
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
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
A Product of Experts Approach to Early-Exit Ensembles
JU Allingham, E Nalisnick
Technical report, 2022
强制性开放获取政策： UK Engineering and Physical Sciences Research Council
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