Richard E Turner
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Variational continual learning
CV Nguyen, Y Li, TD Bui, RE Turner
arXiv preprint arXiv:1710.10628, 2017
Gaussian process behaviour in wide deep neural networks
Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani
International Conference on Learning Representations 4, 2018
Q-prop: Sample-efficient policy gradient with an off-policy critic
S Gu, T Lillicrap, Z Ghahramani, RE Turner, S Levine
arXiv preprint arXiv:1611.02247, 2016
Two problems with variational expectation maximisation for time-series models
RE Turner, M Sahani
Invariant models for causal transfer learning
M Rojas-Carulla, B Schölkopf, R Turner, J Peters
Journal of Machine Learning Research 19 (36), 1-34, 2018
Rényi divergence variational inference
Y Li, RE Turner
Advances in neural information processing systems 29, 2016
Nonlinear ICA using auxiliary variables and generalized contrastive learning
A Hyvarinen, H Sasaki, R Turner
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Meta-learning probabilistic inference for prediction
J Gordon, J Bronskill, M Bauer, S Nowozin, RE Turner
arXiv preprint arXiv:1805.09921, 2018
The processing and perception of size information in speech sounds
DRR Smith, RD Patterson, R Turner, H Kawahara, T Irino
The Journal of the Acoustical Society of America 117 (1), 305-318, 2005
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
Deep Gaussian processes for regression using approximate expectation propagation
T Bui, D Hernández-Lobato, J Hernandez-Lobato, Y Li, R Turner
International conference on machine learning, 1472-1481, 2016
Practical deep learning with Bayesian principles
K Osawa, S Swaroop, MEE Khan, A Jain, R Eschenhagen, RE Turner, ...
Advances in neural information processing systems 32, 2019
Black-box alpha divergence minimization
J Hernandez-Lobato, Y Li, M Rowland, T Bui, D Hernández-Lobato, ...
International conference on machine learning, 1511-1520, 2016
Deterministic variational inference for robust bayesian neural networks
A Wu, S Nowozin, E Meeds, RE Turner, JM Hernandez-Lobato, AL Gaunt
arXiv preprint arXiv:1810.03958, 2018
On sparse variational methods and the Kullback-Leibler divergence between stochastic processes
RETZG Alexander G. Matthews, James Hensman
Proceedings of the 19th International Conference on Artificial Intelligence …, 2016
Interpolated policy gradient: Merging on-policy and off-policy gradient estimation for deep reinforcement learning
SS Gu, T Lillicrap, RE Turner, Z Ghahramani, B Schölkopf, S Levine
Advances in neural information processing systems 30, 2017
A unifying framework for Gaussian process pseudo-point approximations using power expectation propagation
TD Bui, J Yan, RE Turner
Journal of Machine Learning Research 18 (104), 1-72, 2017
Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control
N Jaques, S Gu, D Bahdanau, JM Hernández-Lobato, RE Turner, D Eck
International Conference on Machine Learning, 1645-1654, 2017
Convolutional conditional neural processes
J Gordon, WP Bruinsma, AYK Foong, J Requeima, Y Dubois, RE Turner
arXiv preprint arXiv:1910.13556, 2019
Stochastic expectation propagation
Y Li, JM Hernández-Lobato, RE Turner
Advances in neural information processing systems 28, 2015
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