no code implementations • 2 Dec 2019 • Jack K. Fitzsimons, Sebastian M. Schmon, Stephen J. Roberts
Bayesian interpretations of neural network have a long history, dating back to early work in the 1990's and have recently regained attention because of their desirable properties like uncertainty estimation, model robustness and regularisation.
no code implementations • 1 Apr 2018 • Zhikuan Zhao, Jack K. Fitzsimons, Patrick Rebentrost, Vedran Dunjko, Joseph F. Fitzsimons
Machine learning has recently emerged as a fruitful area for finding potential quantum computational advantage.
no code implementations • 28 Mar 2018 • Zhikuan Zhao, Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph F. Fitzsimons
Gaussian processes (GPs) are important models in supervised machine learning.
no code implementations • 12 Dec 2015 • Zhikuan Zhao, Jack K. Fitzsimons, Joseph F. Fitzsimons
We show that even in some cases not ideally suited to the quantum linear systems algorithm, a polynomial increase in efficiency still occurs.