Seguir
Bobby He
Bobby He
Dirección de correo verificada de inf.ethz.ch - Página principal
Título
Citado por
Citado por
Año
Bayesian deep ensembles via the neural tangent kernel
B He, B Lakshminarayanan, YW Teh
Advances in neural information processing systems 33, 1010-1022, 2020
1332020
Stable resnet
S Hayou, E Clerico, B He, G Deligiannidis, A Doucet, J Rousseau
International Conference on Artificial Intelligence and Statistics, 1324-1332, 2021
542021
Deep transformers without shortcuts: Modifying self-attention for faithful signal propagation
B He, J Martens, G Zhang, A Botev, A Brock, SL Smith, YW Teh
ICLR 2023, 2023
242023
Exploring the gap between collapsed & whitened features in self-supervised learning
B He, M Ozay
International Conference on Machine Learning, 8613-8634, 2022
232022
Simplifying transformer blocks
B He, T Hofmann
ICLR 2024, 2023
222023
The shaped transformer: Attention models in the infinite depth-and-width limit
L Noci, C Li, M Li, B He, T Hofmann, CJ Maddison, D Roy
Advances in Neural Information Processing Systems 36, 2024
212024
Feature kernel distillation
B He, M Ozay
ICLR 2022, 2022
212022
Uncertainr: Uncertainty quantification of end-to-end implicit neural representations for computed tomography
F Vasconcelos, B He, N Singh, YW Teh
TMLR, 2022
172022
Efficient Bayesian inference of instantaneous reproduction numbers at fine spatial scales, with an application to mapping and nowcasting the Covid-19 epidemic in British local …
YW Teh, B Elesedy, B He, M Hutchinson, S Zaidi, A Bhoopchand, ...
Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022
132022
Effectiveness and resource requirements of test, trace and isolate strategies for COVID in the UK
B He, S Zaidi, B Elesedy, M Hutchinson, A Paleyes, G Harling, ...
Royal Society open science 8 (3), 201491, 2021
10*2021
Recurrent Distance Filtering for Graph Representation Learning
Y Ding, A Orvieto, B He, T Hofmann
Forty-first International Conference on Machine Learning, 2024
5*2024
Probabilistic fine-tuning of pruning masks and pac-bayes self-bounded learning
S Hayou, B He, GK Dziugaite
arXiv preprint arXiv:2110.11804, 2021
32021
Understanding and Minimising Outlier Features in Neural Network Training
B He, L Noci, D Paliotta, I Schlag, T Hofmann
arXiv preprint arXiv:2405.19279, 2024
2024
Hallmarks of Optimization Trajectories in Neural Networks and LLMs: The Lengths, Bends, and Dead Ends
SP Singh, B He, T Hofmann, B Schölkopf
arXiv preprint arXiv:2403.07379, 2024
2024
Authors’ Reply to the Discussion of ‘Efficient Bayesian Inference of Instantaneous Reproduction Numbers at Fine Spatial Scales, with an Application to Mapping and Nowcasting …
YW Teh, B Elesedy, B He, M Hutchinson, S Zaidi, A Bhoopchand, ...
Journal of the Royal Statistical Society Series A: Statistics in Society 185 …, 2022
2022
On kernel and feature learning in neural networks
B He
University of Oxford, 2022
2022
Hallmarks of Optimization Trajectories in Neural Networks and LLMs: Directional Exploration and Redundancy
SP Singh, B He, T Hofmann, B Schölkopf
ICML 2024 Workshop on Theoretical Foundations of Foundation Models, 0
Unveiling Grokking: Analyzing Feature Learning Dynamics During Training
JS Baustiste, G Bachmann, B He, L Noci, T Hofmann
High-dimensional Learning Dynamics 2024: The Emergence of Structure and …, 0
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–18