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Jonathan Gordon
Jonathan Gordon
OpenAI
在 openai.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
2982*2023
Meta-learning probabilistic inference for prediction
J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner
arXiv preprint arXiv:1805.09921, 2018
3012018
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 32, 2019
2662019
Convolutional conditional neural processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
arXiv preprint arXiv:1910.13556, 2019
1602019
Bayesian batch active learning as sparse subset approximation
R Pinsler, J Gordon, E Nalisnick, JM Hernández-Lobato
Advances in neural information processing systems 32, 2019
1342019
Tasknorm: Rethinking batch normalization for meta-learning
J Bronskill, J Gordon, J Requeima, S Nowozin, R Turner
International Conference on Machine Learning, 1153-1164, 2020
1142020
Permutation equivariant models for compositional generalization in language
J Gordon, D Lopez-Paz, M Baroni, D Bouchacourt
International Conference on Learning Representations, 2019
1072019
Probabilistic neural architecture search
FP Casale, J Gordon, N Fusi
arXiv preprint arXiv:1902.05116, 2019
842019
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, 8284-8295, 2020
662020
Evolution through large models
J Lehman, J Gordon, S Jain, K Ndousse, C Yeh, KO Stanley
Handbook of Evolutionary Machine Learning, 331-366, 2023
582023
Combining deep generative and discriminative models for Bayesian semi-supervised learning
J Gordon, JM Hernández-Lobato
Pattern Recognition 100, 107156, 2020
582020
The Gaussian neural process
WP Bruinsma, J Requeima, AYK Foong, J Gordon, RE Turner
arXiv preprint arXiv:2101.03606, 2021
342021
Bayesian semisupervised learning with deep generative models
J Gordon, JM Hernández-Lobato
arXiv preprint arXiv:1706.09751, 2017
332017
Insights into amyotrophic lateral sclerosis from a machine learning perspective
J Gordon, B Lerner
Journal of Clinical Medicine 8 (10), 1578, 2019
302019
Predictive complexity priors
E Nalisnick, J Gordon, JM Hernández-Lobato
International Conference on Artificial Intelligence and Statistics, 694-702, 2021
252021
Versa: Versatile and efficient few-shot learning
J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner
Third workshop on Bayesian Deep Learning, 2018
152018
Refining the variational posterior through iterative optimization
M Havasi, J Snoek, D Tran, J Gordon, JM Hernández-Lobato
72021
Advances in Probabilistic Meta-Learning and the Neural Process Family
J Gordon
62021
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
32018
Sampling the variational posterior with local refinement
M Havasi, J Snoek, D Tran, J Gordon, JM Hernández-Lobato
Entropy 23 (11), 1475, 2021
12021
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