Alexander G. de G. Matthews

According to our database1, Alexander G. de G. Matthews authored at least 9 papers between 2015 and 2020.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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On csauthors.net:

Bibliography

2020
Functional Regularisation for Continual Learning with Gaussian Processes.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Ab-Initio Solution of the Many-Electron Schrödinger Equation with Deep Neural Networks.
CoRR, 2019

Functional Regularisation for Continual Learning using Gaussian Processes.
CoRR, 2019

2018
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

2017
GPflow: A Gaussian Process Library using TensorFlow.
J. Mach. Learn. Res., 2017

2016
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes.
Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016

2015
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


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