Jonathan Gordon
Jonathan Gordon
Verified email at cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
Meta-learning probabilistic inference for prediction
J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner
arXiv preprint arXiv:1805.09921, 2018
59*2018
Probabilistic Neural Architecture Search
FP Casale, J Gordon, N Fusi
arXiv preprint arXiv:1902.05116, 2019
232019
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
152019
Bayesian semisupervised learning with deep generative models
J Gordon, JM HernŠndez-Lobato
arXiv preprint arXiv:1706.09751, 2017
152017
Bayesian batch active learning as sparse subset approximation
R Pinsler, J Gordon, E Nalisnick, JM HernŠndez-Lobato
Advances in Neural Information Processing Systems, 6359-6370, 2019
122019
Permutation equivariant models for compositional generalization in language
J Gordon, D Lopez-Paz, M Baroni, D Bouchacourt
International Conference on Learning Representations, 2019
82019
Convolutional Conditional Neural Processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
arXiv preprint arXiv:1910.13556, 2019
72019
Combining deep generative and discriminative models for Bayesian semi-supervised learning
J Gordon, JM HernŠndez-Lobato
Pattern Recognition 100, 107156, 2020
32020
Insights into Amyotrophic Lateral Sclerosis from a Machine Learning Perspective
J Gordon, B Lerner
Journal of Clinical Medicine 8 (10), 1578, 2019
32019
TaskNorm: Rethinking Batch Normalization for Meta-Learning
J Bronskill, J Gordon, J Requeima, S Nowozin, RE Turner
arXiv preprint arXiv:2003.03284, 2020
22020
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
12018
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
12018
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
12016
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes
AYK Foong, WP Bruinsma, J Gordon, Y Dubois, J Requeima, RE Turner
arXiv preprint arXiv:2007.01332, 2020
2020
Predictive Complexity Priors
E Nalisnick, J Gordon, JM HernŠndez-Lobato
arXiv preprint arXiv:2006.10801, 2020
2020
Refining the variational posterior through iterative optimization
M Havasi, J Snoek, D Tran, J Gordon, JM HernŠndez-Lobato
2019
Composing Neural Processes with Flux
WP Bruinsma, J Gordon, RE Turner
Supplementary Material for Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes
J Requeima, J Gordon, J Bronskill, S Nowozin, RE Turner
Bayesian Deep Generative Models for Semi-Supervised and Active Learning
J Gordon
The system can't perform the operation now. Try again later.
Articles 1–19