David Barber

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Aleksandar BotevGoogle DeepmindDirección de correo verificada de google.com
Silvia ChiappaSenior Staff Research Scientist, Google DeepMind; Honorary Professor, UCLDirección de correo verificada de google.com
Mingtian ZhangResearch Fellow, University College LondonDirección de correo verificada de ucl.ac.uk
Ali Taylan CemgilResearch Scientist, DeepMind UKDirección de correo verificada de google.com
Thomas BirdUniversity College LondonDirección de correo verificada de ucl.ac.uk
Peter SollichProfessor Non-Equilibrium Statistical Physics, Inst. for Theor. Physics, University of GoettingenDirección de correo verificada de uni-goettingen.de
Christopher M. BishopTechnical Fellow, Microsoft Research, Cambridge, U.K.Dirección de correo verificada de microsoft.com
Chris WilliamsProfessor of Machine Learning, University of EdinburghDirección de correo verificada de inf.ed.ac.uk
Hilbert Johan KappenRadboud UniversityDirección de correo verificada de science.ru.nl
Wim WiegerinckResearcher machine learning, Radboud University, NijmegenDirección de correo verificada de science.ru.nl
Julius KunzeUniversity College LondonDirección de correo verificada de ucl.ac.uk
Jean-Pascal PfisterProfessor of Theoretical Neuroscience, Department of Physiology, University of BernDirección de correo verificada de unibe.ch
Wulfram GerstnerEPFLDirección de correo verificada de epfl.ch
Joseph JacobUniversity College LondonDirección de correo verificada de ucl.ac.uk
Edward ChallisCEO, ReinferDirección de correo verificada de reinfer.io
Raza HabibUCLDirección de correo verificada de ucl.ac.uk
James TownsendUniversity of AmsterdamDirección de correo verificada de uva.nl
David SaadAston UniversityDirección de correo verificada de aston.ac.uk
Taro ToyoizumiRIKEN Center for Brain ScienceDirección de correo verificada de riken.jp
Ilya FeigeGlobal Head of AI & ML, CerberusDirección de correo verificada de cerberusuk.com

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David Barber

Department of Computer Science, University College London

Dirección de correo verificada de ucl.ac.uk

Machine Learning


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Bayesian reasoning and machine learning D Barber Cambridge University Press, 2012	2614	2012
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	1083	1998
The IM algorithm: a variational approach to information maximization DBF Agakov Advances in neural information processing systems 16 (320), 201, 2004	526*	2004
A scalable laplace approximation for neural networks H Ritter, A Botev, D Barber 6th international conference on learning representations, ICLR 2018 …, 2018	500	2018
Thinking fast and slow with deep learning and tree search T Anthony, Z Tian, D Barber Advances in neural information processing systems 30, 2017	445	2017
Bayesian time series models D Barber, AT Cemgil, S Chiappa Cambridge University Press, 2011	409	2011
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting H Ritter, A Botev, D Barber Neural Information Processing Systems, 2018	360	2018
Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning JP Pfister, T Toyoizumi, D Barber, W Gerstner Neural computation 18 (6), 1318-1348, 2006	309	2006
Ensemble learning in Bayesian neural networks D Barber, CM Bishop Nato ASI Series F Computer and Systems Sciences 168, 215-238, 1998	298	1998
Practical Gauss-Newton optimisation for deep learning A Botev, H Ritter, D Barber International Conference on Machine Learning, 557-565, 2017	269	2017
Nesterov's accelerated gradient and momentum as approximations to regularised update descent A Botev, G Lever, D Barber 2017 International joint conference on neural networks (IJCNN), 1899-1903, 2017	204	2017
A generative model for music transcription AT Cemgil, HJ Kappen, D Barber IEEE Transactions on Audio, Speech, and Language Processing 14 (2), 679-694, 2006	185	2006
Practical Lossless Compression with Latent Variables using Bits Back Coding james townsend	167	2019
Thermodynamics of rock deformation by pressure solution DJ Barber, PG Meredith, FK Lehner Deformation processes in minerals, ceramics and rocks, 296-333, 1990	150	1990
Modular networks: Learning to decompose neural computation L Kirsch, J Kunze, D Barber Advances in neural information processing systems 31, 2018	141	2018
Computed tomographic biomarkers in idiopathic pulmonary fibrosis. The future of quantitative analysis X Wu, GH Kim, ML Salisbury, D Barber, BJ Bartholmai, KK Brown, ... American journal of respiratory and critical care medicine 199 (1), 12-21, 2019	140	2019
Ensemble learning for multi-layer networks D Barber, C Bishop Advances in neural information processing systems 10, 1997	125	1997
Gaussian processes for Bayesian classification via hybrid Monte Carlo D Barber, C Williams Advances in neural information processing systems 9, 1996	114	1996
Expectation correction for smoothed inference in switching linear dynamical systems. D Barber Journal of Machine Learning Research 7 (11), 2006	111	2006
On the computational complexity of stochastic controller optimization in POMDPs N Vlassis, ML Littman, D Barber ACM Transactions on Computation Theory (TOCT) 4 (4), 1-8, 2012	110	2012

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