Bayesian reasoning and machine learning D Barber Cambridge University Press, 2012 | 2453 | 2012 |
Bayesian classification with Gaussian processes CKI Williams, D Barber IEEE Transactions on pattern analysis and machine intelligence 20 (12), 1342 …, 1998 | 1036 | 1998 |
The IM algorithm: a variational approach to information maximization DBF Agakov Advances in neural information processing systems 16 (320), 201, 2004 | 477* | 2004 |
A scalable laplace approximation for neural networks H Ritter, A Botev, D Barber 6th international conference on learning representations, ICLR 2018 …, 2018 | 428 | 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 | 396 | 2017 |
Bayesian time series models D Barber, AT Cemgil, S Chiappa Cambridge University Press, 2011 | 391 | 2011 |
Online Structured Laplace Approximations for Overcoming Catastrophic Forgetting H Ritter, A Botev, D Barber Neural Information Processing Systems, 2018 | 306 | 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 | 301 | 2006 |
Ensemble learning in Bayesian neural networks D Barber, CM Bishop Nato ASI Series F Computer and Systems Sciences 168, 215-238, 1998 | 280 | 1998 |
Practical Gauss-Newton optimisation for deep learning A Botev, H Ritter, D Barber International Conference on Machine Learning, 557-565, 2017 | 232 | 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 | 184 | 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 | 183 | 2006 |
Thermodynamics of rock deformation by pressure solution DJ Barber, PG Meredith, FK Lehner Deformation processes in minerals, ceramics and rocks, 296-333, 1990 | 148 | 1990 |
Practical Lossless Compression with Latent Variables using Bits Back Coding james townsend | 140 | 2019 |
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 | 129 | 2019 |
Modular networks: Learning to decompose neural computation L Kirsch, J Kunze, D Barber Advances in neural information processing systems 31, 2018 | 127 | 2018 |
Ensemble learning for multi-layer networks D Barber, C Bishop Advances in neural information processing systems 10, 1997 | 121 | 1997 |
Gaussian processes for Bayesian classification via hybrid Monte Carlo D Barber, C Williams Advances in neural information processing systems 9, 1996 | 110 | 1996 |
Expectation correction for smoothed inference in switching linear dynamical systems. D Barber Journal of Machine Learning Research 7 (11), 2006 | 108 | 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 | 103 | 2012 |