Jonathan Gordon

Publication Activity (10 Years)

Years Active: 2018-2021
Publications (10 Years): 19

Top Topics

Discriminative Models

Stochastic Process

Top Venues

Publications

Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato
Sampling the Variational Posterior with Local Refinement. Entropy 23 (11) (2021)
Eric T. Nalisnick, Jonathan Gordon, José Miguel Hernández-Lobato
Predictive Complexity Priors. AISTATS (2021)
Wessel P. Bruinsma, James Requeima, Andrew Y. K. Foong, Jonathan Gordon, Richard E. Turner
The Gaussian Neural Process. CoRR (2021)
Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt
Permutation Equivariant Models for Compositional Generalization in Language. ICLR (2020)
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
TaskNorm: Rethinking Batch Normalization for Meta-Learning. CoRR (2020)
Andrew Y. K. Foong, Wessel P. Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. CoRR (2020)
Jonathan Gordon, José Miguel Hernández-Lobato
Combining deep generative and discriminative models for Bayesian semi-supervised learning. Pattern Recognit. 100 (2020)
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner
Convolutional Conditional Neural Processes. ICLR (2020)
John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard E. Turner
TaskNorm: Rethinking Batch Normalization for Meta-Learning. ICML (2020)
Andrew Y. K. Foong, Wessel Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard E. Turner
Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes. NeurIPS (2020)
Eric T. Nalisnick, Jonathan Gordon, José Miguel Hernández-Lobato
Predictive Complexity Priors. CoRR (2020)
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner
Meta-Learning Probabilistic Inference for Prediction. ICLR (Poster) (2019)
Francesco Paolo Casale, Jonathan Gordon, Nicoló Fusi
Probabilistic Neural Architecture Search. CoRR (2019)
Robert Pinsler, Jonathan Gordon, Eric T. Nalisnick, José Miguel Hernández-Lobato
Bayesian Batch Active Learning as Sparse Subset Approximation. NeurIPS (2019)
Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner
Convolutional Conditional Neural Processes. CoRR (2019)
Robert Pinsler, Jonathan Gordon, Eric T. Nalisnick, José Miguel Hernández-Lobato
Bayesian Batch Active Learning as Sparse Subset Approximation. CoRR (2019)
James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
Fast and Flexible Multi-Task Classification using Conditional Neural Adaptive Processes. NeurIPS (2019)
James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E. Turner
Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes. CoRR (2019)
Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard E. Turner
Decision-Theoretic Meta-Learning: Versatile and Efficient Amortization of Few-Shot Learning. CoRR (2018)