David Barber

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Silvia ChiappaSenior Staff Research Scientist, DeepMind; Honorary Professor, UCLVerified email at google.com
Aleksandar BotevGoogle DeepmindVerified email at google.com
Ali Taylan CemgilResearch Scientist, DeepMind UKVerified email at google.com
Hippolyt RitterUniversity College LondonVerified email at cs.ucl.ac.uk
Peter SollichProfessor of Non-Equilibrium Statistical PhysicsVerified email at uni-goettingen.de
Thomas BirdUniversity College LondonVerified email at ucl.ac.uk
Chris WilliamsProfessor of Machine Learning, University of EdinburghVerified email at inf.ed.ac.uk
Christopher M. BishopDistinguished Scientist, Microsoft Research, Cambridge, U.K.Verified email at microsoft.com
Hilbert Johan KappenRadboud UniversityVerified email at science.ru.nl
Wim WiegerinckResearcher machine learning, Radboud University, NijmegenVerified email at science.ru.nl
Jean-Pascal PfisterProfessor of Theoretical Neuroscience, Institute of Neuroinformatics, University of Zurich and ETHVerified email at ini.uzh.ch
Wulfram GerstnerEPFLVerified email at epfl.ch
Julius KunzeUniversity College LondonVerified email at ucl.ac.uk
David SaadAston UniversityVerified email at aston.ac.uk
Raza HabibUCLVerified email at ucl.ac.uk
Mingtian ZhangPhD student, University College LondonVerified email at ucl.ac.uk
Taro ToyoizumiRIKEN Center for Brain ScienceVerified email at riken.jp
James TownsendUniversity of AmsterdamVerified email at uva.nl
Guy LeverVerified email at google.com
Louis KirschThe Swiss AI Lab IDSIAVerified email at idsia.ch

David Barber

Department of Computer Science, University College London

Verified email at ucl.ac.uk

Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Bayesian reasoning and machine learning D Barber Cambridge University Press, 2012	2039	2012
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998	913	1998
The IM algorithm: a variational approach to information maximization DBF Agakov Advances in neural information processing systems 16 (320), 201, 2004	316	2004
Bayesian time series models D Barber, AT Cemgil, S Chiappa Cambridge University Press, 2011	307	2011
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	279	2006
Thinking fast and slow with deep learning and tree search T Anthony, Z Tian, D Barber Advances in Neural Information Processing Systems 30, 2017	257	2017
Ensemble learning in Bayesian neural networks D Barber, CM Bishop Nato ASI Series F Computer and Systems Sciences 168, 215-238, 1998	212	1998
A scalable laplace approximation for neural networks H Ritter, A Botev, D Barber 6th International Conference on Learning Representations, ICLR 2018 …, 2018	202	2018
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting H Ritter, A Botev, D Barber Neural Information Processing Systems, 2018	174	2018
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	163	2006
Practical gauss-newton optimisation for deep learning A Botev, H Ritter, D Barber International Conference on Machine Learning, 557-565, 2017	140	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	108	2017
Ensemble learning for multi-layer networks D Barber, C Bishop Advances in neural information processing systems 10, 1997	107	1997
Gaussian processes for Bayesian classification via hybrid Monte Carlo D Barber, C Williams Advances in neural information processing systems 9, 1996	105	1996
Expectation correction for smoothed inference in switching linear dynamical systems. D Barber Journal of Machine Learning Research 7 (11), 2006	97	2006
Switching linear dynamical systems for noise robust speech recognition B Mesot, D Barber IEEE Transactions on Audio, Speech, and Language Processing 15 (6), 1850-1858, 2007	82	2007
Graphical models for time-series D Barber, AT Cemgil IEEE Signal Processing Magazine 27 (6), 18-28, 2010	80	2010
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	79	2019
Practical Lossless Compression with Latent Variables using Bits Back Coding james townsend	78	2019
An auxiliary variational method FV Agakov, D Barber International Conference on Neural Information Processing, 561-566, 2004	74	2004

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