Gaussian processes in machine learning CE Rasmussen Summer school on machine learning, 63-71, 2003 | 33253 | 2003 |
Gaussian processes for machine learning CKI Williams, CE Rasmussen MIT press 2 (3), 4, 2006 | 3960 | 2006 |
Proceedings of the 31st International Conference on Neural Information Processing Systems U von Luxburg, I Guyon, S Bengio, H Wallach, R Fergus Curran Associates Inc., 2017 | 3203* | 2017 |
Automatic chemical design using a data-driven continuous representation of molecules R Gómez-Bombarelli, JN Wei, D Duvenaud, JM Hernández-Lobato, ... ACS central science 4 (2), 268-276, 2018 | 3092 | 2018 |
Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons AP Bartók, MC Payne, R Kondor, G Csányi Physical review letters 104 (13), 136403, 2010 | 2476 | 2010 |
Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources TW Lee, M Girolami, TJ Sejnowski Neural computation 11 (2), 417-441, 1999 | 2459 | 1999 |
A unifying view of sparse approximate Gaussian process regression J Quinonero-Candela, CE Rasmussen The Journal of Machine Learning Research 6, 1939-1959, 2005 | 2458 | 2005 |
Nice: Non-linear independent components estimation L Dinh, D Krueger, Y Bengio arXiv preprint arXiv:1410.8516, 2014 | 2191 | 2014 |
Dataset shift in machine learning J Quiñonero-Candela, M Sugiyama, A Schwaighofer, ND Lawrence Mit Press, 2022 | 2165 | 2022 |
On representing chemical environments AP Bartók, R Kondor, G Csányi Physical Review B 87 (18), 184115, 2013 | 2160 | 2013 |
PILCO: A model-based and data-efficient approach to policy search M Deisenroth, CE Rasmussen Proceedings of the 28th International Conference on machine learning (ICML …, 2011 | 1906 | 2011 |
Riemann manifold langevin and hamiltonian monte carlo methods M Girolami, B Calderhead Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2011 | 1883 | 2011 |
A closer look at memorization in deep networks D Arpit, S Jastrzębski, N Ballas, D Krueger, E Bengio, MS Kanwal, ... International conference on machine learning, 233-242, 2017 | 1823 | 2017 |
The infinite Gaussian mixture model C Rasmussen Advances in neural information processing systems 12, 1999 | 1798 | 1999 |
Gaussian processes for regression C Williams, C Rasmussen Advances in neural information processing systems 8, 1995 | 1788 | 1995 |
Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial RECOVERY Collaborative Group Lancet (London, England) 397 (10285), 1637, 2021 | 1631* | 2021 |
Simlex-999: Evaluating semantic models with (genuine) similarity estimation F Hill, R Reichart, A Korhonen Computational Linguistics 41 (4), 665-695, 2015 | 1530 | 2015 |
Gaussian processes for big data J Hensman, N Fusi, ND Lawrence arXiv preprint arXiv:1309.6835, 2013 | 1421 | 2013 |
Deep gaussian processes A Damianou, ND Lawrence Artificial intelligence and statistics, 207-215, 2013 | 1372 | 2013 |
Probabilistic non-linear principal component analysis with Gaussian process latent variable models. N Lawrence, A Hyvärinen Journal of machine learning research 6 (11), 2005 | 1320 | 2005 |