עקוב אחר
Alexander G. D. G. Matthews
Alexander G. D. G. Matthews
DeepMind
כתובת אימייל מאומתת בדומיין google.com
כותרת
צוטט על ידי
צוטט על ידי
שנה
Scalable Variational Gaussian Process Classification.‏
J Hensman, A Matthews, Z Ghahramani‏
The 18th International Conference on Artificial Intelligence and Statistics …, 2015‏
7802015
GPflow: A Gaussian process library using TensorFlow‏
AGG Matthews, M van der Wilk, T Nickson, K Fujii, A Boukouvalas, ...‏
Journal of Machine Learning Research 18 (40), 1-6, 2017‏
744*2017
Ab-Initio Solution of the Many-Electron Schr\" odinger Equation with Deep Neural Networks‏
D Pfau, JS Spencer, AGG Matthews, WMC Foulkes‏
arXiv preprint arXiv:1909.02487, 2019‏
5972019
Gaussian Process Behaviour in Wide Deep Neural Networks‏
AGG Matthews, J Hron, M Rowland, RE Turner, Z Ghahramani‏
International Conference on Learning Representations (ICLR), 2018‏
595*2018
Pushing the frontiers of density functionals by solving the fractional electron problem‏
J Kirkpatrick, B McMorrow, DHP Turban, AL Gaunt, JS Spencer, ...‏
Science 374 (6573), 1385-1389, 2021‏
3252021
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes‏
AGG Matthews, J Hensman, RE Turner, Z Ghahramani‏
The 19th International Conference on Artificial Intelligence and Statistics …, 2016‏
217*2016
Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks‏
J Bradshaw, AGG Matthews, Z Ghahramani‏
arXiv preprint arXiv:1707.02476, 2017‏
2042017
Functional Regularisation for Continual Learning with Gaussian Processes‏
MK Titsias, J Schwarz, AGG Matthews, R Pascanu, YW Teh‏
International Conference on Learning Representations, 2019‏
1882019
MCMC for variationally sparse Gaussian processes‏
J Hensman, AG Matthews, M Filippone, Z Ghahramani‏
Advances in Neural Information Processing Systems, 1648-1656, 2015‏
1742015
Measurement and simulation of the effect of compaction on the pore structure and saturated hydraulic conductivity of grassland and arable soil‏
GP Matthews, GM Laudone, AS Gregory, NRA Bird, AG de G Matthews, ...‏
Water Resources Research 46 (5), 2010‏
85*2010
Variational Bayesian dropout: pitfalls and fixes‏
J Hron, A Matthews, Z Ghahramani‏
Proceedings of Machine Learning Research, 2018‏
832018
Scalable Gaussian process inference using variational methods‏
AGG Matthews‏
University of Cambridge, 2017‏
762017
Annealed flow transport monte carlo‏
M Arbel, A Matthews, A Doucet‏
International Conference on Machine Learning, 318-330, 2021‏
652021
Variational Gaussian Dropout is not Bayesian‏
J Hron, AGG Matthews, Z Ghahramani‏
arXiv preprint arXiv:1711.02989, 2017‏
622017
Score-based diffusion meets annealed importance sampling‏
A Doucet, W Grathwohl, AG Matthews, H Strathmann‏
Advances in Neural Information Processing Systems 35, 21482-21494, 2022‏
36*2022
Continual Repeated Annealed Flow transport Monte Carlo‏
A Matthews, M Arbel, DJ Rezende, A Doucet‏
International Conference on Machine Learning, 15196-15219, 2022‏
352022
Sample-then-optimize posterior sampling for bayesian linear models‏
AGG Matthews, J Hron, RE Turner, Z Ghahramani‏
NeurIPS Workshop on Advances in Approximate Bayesian Inference, 2017‏
312017
Aspects of scaling and scalability for flow-based sampling of lattice QCD‏
R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ...‏
The European Physical Journal A 59 (11), 257, 2023‏
252023
Sampling QCD field configurations with gauge-equivariant flow models‏
R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ...‏
arXiv preprint arXiv:2208.03832, 2022‏
202022
Normalizing flows for lattice gauge theory in arbitrary space-time dimension‏
R Abbott, MS Albergo, A Botev, D Boyda, K Cranmer, DC Hackett, ...‏
arXiv preprint arXiv:2305.02402, 2023‏
182023
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–20