| 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 | 107 | 2020 |
| 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 | 44* | 2020 |
| 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 | 40 | 2021 |
| 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 | 33 | 2020 |
| 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 | 29 | 2021 |
| 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 | 20 | 2021 |
| Trieste: Efficiently exploring the depths of black-box functions with TensorFlow V Picheny, J Berkeley, HB Moss, H Stojic, U Granta, SW Ober, A Artemev, ... arXiv preprint arXiv:2302.08436, 2023 | 12 | 2023 |
| Combined modelling of mRNA decay dynamics and single-molecule imaging in the Drosophila embryo uncovers a role for P-bodies in 5′ to 3′ degradation L Forbes Beadle, JC Love, Y Shapovalova, A Artemev, M Rattray, ... PLoS Biology 21 (1), e3001956, 2023 | 12 | 2023 |
| Ordinal bayesian optimisation V Picheny, S Vakili, A Artemev arXiv preprint arXiv:1912.02493, 2019 | 7 | 2019 |
| 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 | 7 | 2019 |
| Memory safe computations with XLA compiler A Artemev, Y An, T Roeder, M van der Wilk Advances in Neural Information Processing Systems 35, 18970-18982, 2022 | 6 | 2022 |
| Uri Granta, Hrvoje Stojic, Ivo Couckuyt, Jixiang Qing, Nasrulloh Loka, Andrei Paleyes, Sebastian W. Ober, and Victor Picheny. Trieste J Berkeley, HB Moss, A Artemev, S Pascual-Diaz | 6 | 2022 |
| Computational implementation of gaussian process models M VAN DER WILK, S John, A Artemev, J Hensman US Patent 11,475,279, 2022 | 5 | 2022 |
| Numerically stable sparse gaussian processes via minimum separation using cover trees A Terenin, DR Burt, A Artemev, S Flaxman, M van der Wilk, ... Journal of Machine Learning Research 25, 1-36, 2024 | 2 | 2024 |
| Modelling global mRNA dynamics during Drosophila embryogenesis reveals a relationship between mRNA degradation and P-bodies LF Beadle, JC Love, Y Shapovalova, A Artemev, M Rattray, HL Ashe bioRxiv, 2022.03. 17.484585, 2022 | 2 | 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, 2022 | 2 | 2022 |
| Barely biased learning for gaussian process regression DR Burt, A Artemev, M van der Wilk arXiv preprint arXiv:2109.09417, 2021 | 2 | 2021 |
| Automatic tuning of stochastic gradient descent with Bayesian optimisation V Picheny, V Dutordoir, A Artemev, N Durrande Machine Learning and Knowledge Discovery in Databases: European Conference …, 2021 | 2 | 2021 |
| Recommendations for Baselines and Benchmarking Approximate Gaussian Processes SW Ober, A Artemev, M Wagenländer, R Grobins, M van der Wilk arXiv preprint arXiv:2402.09849, 2024 | 1 | 2024 |
| Efficient computational inference V Adam, S Eleftheriadis, N Durrande, A Artemev, J Hensman, L Bordeaux US Patent App. 17/753,723, 2022 | 1 | 2022 |
Mark van der WilkAssociate Professor, University of OxfordZweryfikowany adres z cs.ox.ac.uk
