Alexander G. de G. Matthews

Affiliations:
  • DeepMind
  • University of Cambridge, Department of Engineering (former)


According to our database1, Alexander G. de G. Matthews authored at least 14 papers between 2015 and 2023.

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

Timeline

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Bibliography

2023
Normalizing flows for lattice gauge theory in arbitrary space-time dimension.
CoRR, 2023

2022
Aspects of scaling and scalability for flow-based sampling of lattice QCD.
CoRR, 2022

Score-Based Diffusion meets Annealed Importance Sampling.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Continual Repeated Annealed Flow Transport Monte Carlo.
Proceedings of the International Conference on Machine Learning, 2022

2021
Annealed Flow Transport Monte Carlo.
Proceedings of the 38th International Conference on Machine Learning, 2021

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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