| Meta-learning probabilistic inference for prediction J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner arXiv preprint arXiv:1805.09921, 2018 | 83 | 2018 |
| Probabilistic Neural Architecture Search FP Casale, J Gordon, N Fusi arXiv preprint arXiv:1902.05116, 2019 | 35 | 2019 |
| Fast and flexible multi-task classification using conditional neural adaptive processes J Requeima, J Gordon, J Bronskill, S Nowozin, RE Turner Advances in Neural Information Processing Systems, 7959-7970, 2019 | 21 | 2019 |
| Bayesian batch active learning as sparse subset approximation R Pinsler, J Gordon, E Nalisnick, JM Hernández-Lobato Advances in Neural Information Processing Systems, 6359-6370, 2019 | 20 | 2019 |
| Permutation equivariant models for compositional generalization in language J Gordon, D Lopez-Paz, M Baroni, D Bouchacourt International Conference on Learning Representations, 2019 | 17 | 2019 |
| Bayesian semisupervised learning with deep generative models J Gordon, JM Hernández-Lobato arXiv preprint arXiv:1706.09751, 2017 | 16 | 2017 |
| Convolutional Conditional Neural Processes J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner arXiv preprint arXiv:1910.13556, 2019 | 14 | 2019 |
| Combining deep generative and discriminative models for Bayesian semi-supervised learning J Gordon, JM Hernández-Lobato Pattern Recognition 100, 107156, 2020 | 9 | 2020 |
| TaskNorm: Rethinking Batch Normalization for Meta-Learning J Bronskill, J Gordon, J Requeima, S Nowozin, RE Turner arXiv preprint arXiv:2003.03284, 2020 | 8 | 2020 |
| Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes A Foong, W Bruinsma, J Gordon, Y Dubois, J Requeima, R Turner Advances in Neural Information Processing Systems 33, 2020 | 3 | 2020 |
| Insights into Amyotrophic Lateral Sclerosis from a Machine Learning Perspective J Gordon, B Lerner Journal of Clinical Medicine 8 (10), 1578, 2019 | 3 | 2019 |
| Predictive Complexity Priors E Nalisnick, J Gordon, JM Hernández-Lobato arXiv preprint arXiv:2006.10801, 2020 | 1 | 2020 |
| Refining the variational posterior through iterative optimization M Havasi, J Snoek, D Tran, J Gordon, JM Hernández-Lobato | 1 | 2019 |
| VERSA: Versatile and Efficient Few-shot Learning J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner Advances in Neural Information Processing Systems, 1-9, 2018 | 1 | 2018 |
| Consolidating the Meta-Learning Zoo: A Unifying Perspective as Posterior Predictive Inference J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner Workshop on Meta-Learning (MetaLearn 2018) at the 32nd Conference on Neural …, 2018 | 1 | 2018 |
| Exposing and modeling underlying mechanisms in ALS with machine learning J Gordon, B Lerner 2016 23rd International Conference on Pattern Recognition (ICPR), 2168-2173, 2016 | 1 | 2016 |
| Composing Neural Processes with Flux WP Bruinsma, J Gordon, RE Turner | | |
| Bayesian Deep Generative Models for Semi-Supervised and Active Learning J Gordon | | |
Richard E TurnerProfessor, University of CambridgeVerified email at cam.ac.uk
