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Artem Artemev
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A framework for interdomain and multioutput Gaussian processes
M van der Wilk, V Dutordoir, ST John, A Artemev, V Adam, J Hensman
arXiv preprint arXiv:2003.01115, 2020
462020
Bayesian image classification with deep convolutional Gaussian processes
V Dutordoir, M Wilk, A Artemev, J Hensman
International Conference on Artificial Intelligence and Statistics, 1529-1539, 2020
29*2020
Doubly Sparse Variational Gaussian Processes
V Adam, S Eleftheriadis, N Durrande, A Artemev, J Hensman
The 23rd International Conference on Artificial Intelligence and Statistics, 2020
142020
Scalable Thompson sampling using sparse Gaussian process models
S Vakili, H Moss, A Artemev, V Dutordoir, V Picheny
Advances in Neural Information Processing Systems 34, 5631-5643, 2021
102021
GPflux: A library for deep Gaussian processes
V Dutordoir, H Salimbeni, E Hambro, J McLeod, F Leibfried, A Artemev, ...
arXiv preprint arXiv:2104.05674, 2021
92021
Tighter bounds on the log marginal likelihood of Gaussian process regression using conjugate gradients
A Artemev, DR Burt, M Van Der Wilk
International Conference on Machine Learning, 362-372, 2021
52021
Variational Gaussian Process Models without Matrix Inverses
M van der Wilk, ST John, A Artemev, J Hensman
2nd Symposium on Advances in Approximate Bayesian Inference, 2019
42019
Ordinal bayesian optimisation
V Picheny, S Vakili, A Artemev
arXiv preprint arXiv:1912.02493, 2019
32019
Automatic tuning of stochastic gradient descent with bayesian optimisation
V Picheny, V Dutordoir, A Artemev, N Durrande
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020
12020
Memory Safe Computations with XLA Compiler
A Artemev, T Roeder, M van der Wilk
arXiv preprint arXiv:2206.14148, 2022
2022
Computational implementation of gaussian process models
M VAN DER WILK, S John, A Artemev, J Hensman
US Patent App. 17/643,315, 2022
2022
Improved Inverse-Free Variational Bounds for Sparse Gaussian Processes
M van der Wilk, A Artemev, J Hensman
Fourth Symposium on Advances in Approximate Bayesian Inference, 2021
2021
Barely Biased Learning for Gaussian Process Regression
DR Burt, A Artemev, M van der Wilk
arXiv preprint arXiv:2109.09417, 2021
2021
Placement Project: Sparse State inference for GPSSM and SDE latent models
V Adam, A Artemev
2019
GPflux: ALibraryforDeepGaussianProcesses
V Dutordoir, H Salimbeni, E Hambro, J McLeod, F Leibfried, A Artemev, ...
Supplement: Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression using Conjugate Gradients
A Artemev, DR Burt, M van der Wilk
A Framework for Interdomain and Multioutput Gaussian Processes Download PDF Open Website
M van der Wilk, V Dutordoir, ST John, A Artemev, V Adam, J Hensman
Doubly Sparse Variational Gaussian Processes Download PDF Open Website
V Adam, S Eleftheriadis, A Artemev, N Durrande, J Hensman
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