Tom Gunter
Tom Gunter
Department of Engineering Science, University of Oxford
Verified email at robots.ox.ac.uk
Title
Cited by
Cited by
Year
Variational inference for Gaussian process modulated Poisson processes
C Lloyd, T Gunter, M Osborne, S Roberts
International Conference on Machine Learning, 1814-1822, 2015
1012015
Sampling for inference in probabilistic models with fast Bayesian quadrature
T Gunter, MA Osborne, R Garnett, P Hennig, SJ Roberts
Advances in neural information processing systems, 2789-2797, 2014
862014
Efficient Bayesian nonparametric modelling of structured point processes
T Gunter, C Lloyd, MA Osborne, SJ Roberts
arXiv preprint arXiv:1407.6949, 2014
302014
Blitzkriging: Kronecker-structured stochastic Gaussian processes
T Nickson, T Gunter, C Lloyd, MA Osborne, S Roberts
arXiv preprint arXiv:1510.07965, 2015
182015
Latent point process allocation
C Lloyd, T Gunter, M Osborne, S Roberts, T Nickson
Artificial Intelligence and Statistics, 389-397, 2016
142016
Unknowable manipulators: Social network curator algorithms
S Albanie, H Shakespeare, T Gunter
arXiv preprint arXiv:1701.04895, 2017
72017
Towards efficient Bayesian inference: Cox processes and probabilistic integration
T Gunter
University of Oxford, 2017
2017
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