| Do deep generative models know what they don't know? E Nalisnick, A Matsukawa, YW Teh, D Gorur, B Lakshminarayanan arXiv preprint arXiv:1810.09136, 2018 | 830 | 2018 |
| Stick-breaking construction for the Indian buffet process YW Teh, D Grür, Z Ghahramani Artificial intelligence and statistics, 556-563, 2007 | 367 | 2007 |
| Dirichlet process gaussian mixture models: Choice of the base distribution D Görür, C Edward Rasmussen Journal of Computer Science and Technology 25 (4), 653-664, 2010 | 309 | 2010 |
| Indian buffet processes with power-law behavior Y Teh, D Gorur Advances in neural information processing systems 22, 2009 | 144 | 2009 |
| Linear mode connectivity in multitask and continual learning SI Mirzadeh, M Farajtabar, D Gorur, R Pascanu, H Ghasemzadeh arXiv preprint arXiv:2010.04495, 2020 | 126 | 2020 |
| Hybrid models with deep and invertible features E Nalisnick, A Matsukawa, YW Teh, D Gorur, B Lakshminarayanan International Conference on Machine Learning, 4723-4732, 2019 | 98 | 2019 |
| Sleep spindles detection using short time Fourier transform and neural networks D Gorur, U Halici, H Aydin, G Ongun, F Ozgen, K Leblebicioglu Proceedings of the 2002 International Joint Conference on Neural Networks …, 2002 | 76 | 2002 |
| A choice model with infinitely many latent features D Görür, F Jäkel, CE Rasmussen Proceedings of the 23rd international conference on Machine learning, 361-368, 2006 | 70 | 2006 |
| Architecture matters in continual learning SI Mirzadeh, A Chaudhry, D Yin, T Nguyen, R Pascanu, D Gorur, ... arXiv preprint arXiv:2202.00275, 2022 | 69 | 2022 |
| Wide neural networks forget less catastrophically SI Mirzadeh, A Chaudhry, D Yin, H Hu, R Pascanu, D Gorur, M Farajtabar International Conference on Machine Learning, 15699-15717, 2022 | 65 | 2022 |
| Infinite hierarchical hidden Markov models K Heller, YW Teh, D Gorur Artificial intelligence and statistics, 224-231, 2009 | 63 | 2009 |
| Concave-convex adaptive rejection sampling D Görür, YW Teh Journal of Computational and Graphical Statistics 20 (3), 670-691, 2011 | 59 | 2011 |
| Dependent Dirichlet process spike sorting J Gasthaus, F Wood, D Gorur, Y Teh Advances in neural information processing systems 21, 2008 | 51 | 2008 |
| An Efficient Sequential Monte Carlo Algorithm for Coalescent Clustering D Görür, YW Teh Advances in Neural Information Processing Systems 21, 521-528, 2009 | 32 | 2009 |
| Nonparametric Bayesian discrete latent variable models for unsupervised learning D Görür | 25 | 2007 |
| One pass imagenet H Hu, A Li, D Calandriello, D Gorur arXiv preprint arXiv:2111.01956, 2021 | 17 | 2021 |
| Modelling spikes with mixtures of factor analysers D Görür, CE Rasmussen, AS Tolias, F Sinz, NK Logothetis Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 …, 2004 | 15 | 2004 |
| Sleep spindles detection using autoregressive modeling D Görür, U Halici, H Aydin, G Ongun, F Ozgen, K Leblebicioglu Proceedings of the International Conference on Artificial Neural Networks …, 2003 | 15 | 2003 |
| Towards responsible development of generative AI for education: An evaluation-driven approach I Jurenka, M Kunesch, KR McKee, D Gillick, S Zhu, S Wiltberger, SM Phal, ... arXiv preprint arXiv:2407.12687, 2024 | 14 | 2024 |
| Automated detection of sleep spindles D Görür Middle East Technical University, 2003 | 14 | 2003 |
Yee Whye TehProfessor of Statistical Machine Learning, Oxford, Research Scientist, DeepMindE-mail megerősítve itt: stats.ox.ac.uk
