Gordon, Jonathan

9 publications

AISTATS 2021 Predictive Complexity Priors Eric Nalisnick, Jonathan Gordon, Jose Miguel Hernandez-Lobato

ICLR 2020 Convolutional Conditional Neural Processes Jonathan Gordon, Wessel P. Bruinsma, Andrew Y. K. Foong, James Requeima, Yann Dubois, Richard E. Turner

NeurIPS 2020 Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes Andrew Foong, Wessel Bruinsma, Jonathan Gordon, Yann Dubois, James Requeima, Richard Turner

ICLR 2020 Permutation Equivariant Models for Compositional Generalization in Language Jonathan Gordon, David Lopez-Paz, Marco Baroni, Diane Bouchacourt

ICML 2020 TaskNorm: Rethinking Batch Normalization for Meta-Learning John Bronskill, Jonathan Gordon, James Requeima, Sebastian Nowozin, Richard Turner

NeurIPS 2019 Bayesian Batch Active Learning as Sparse Subset Approximation Robert Pinsler, Jonathan Gordon, Eric Nalisnick, José Miguel Hernández-Lobato

NeurIPS 2019 Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes James Requeima, Jonathan Gordon, John Bronskill, Sebastian Nowozin, Richard E Turner

AAAI 2019 Linking Educational Resources on Data Science José Luis Ambite, Jonathan Gordon, Lily Fierro, Gully Burns, Joel Mathew

ICLR 2019 Meta-Learning Probabilistic Inference for Prediction Jonathan Gordon, John Bronskill, Matthias Bauer, Sebastian Nowozin, Richard Turner