Alexander G. de G. Matthews
According to our database1, Alexander G. de G. Matthews authored at least 9 papers between 2015 and 2020.
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Functional Regularisation for Continual Learning with Gaussian Processes.
Proceedings of the 8th International Conference on Learning Representations, 2020
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks.
Functional Regularisation for Continual Learning using Gaussian Processes.
Variational Bayesian dropout: pitfalls and fixes.
Proceedings of the 35th International Conference on Machine Learning, 2018
Gaussian Process Behaviour in Wide Deep Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018
GPflow: A Gaussian Process Library using TensorFlow.
J. Mach. Learn. Res., 2017
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016
MCMC for Variationally Sparse Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
Scalable Variational Gaussian Process Classification.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015