341 citations · 669 across the 12 of their papers we have counts for
13 papers
The Born Ultimatum: Conditions for Classical Surrogation of Quantum Generative Models with Correlators
Mario Herrero-Gonzalez, Brian Coyle, Kieran McDowall +4
Quantum Circuit Born Machines (QCBMs) are powerful quantum generative models that sample according to the Born rule, with complexity-theoretic evidence suggesting potential quantum…
Machine learning applications for noisy intermediate-scale quantum computers
Brian Coyle
Quantum machine learning has proven to be a fruitful area in which to search for potential applications of quantum computers. This is particularly true for those available in the n…
Information-Theoretic Limits of Quantum Learning via Data Compression
Armando Angrisani, Brian Coyle, Elham Kashefi
Understanding the power of quantum data in machine learning is central to many proposed applications of quantum technologies. While access to quantum data can offer exponential adv…
Graph neural network initialisation of quantum approximate optimisation
Nishant Jain, Brian Coyle, Elham Kashefi +1
Approximate combinatorial optimisation has emerged as one of the most promising application areas for quantum computers, particularly those in the near term. In this work, we focus…
F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits
Chiara Leadbeater, Louis Sharrock, Brian Coyle +1
Generative modelling is an important unsupervised task in machine learning. In this work, we study a hybrid quantum-classical approach to this task, based on the use of a quantum c…
Variational inference with a quantum computer
Marcello Benedetti, Brian Coyle, Mattia Fiorentini +2
Inference is the task of drawing conclusions about unobserved variables given observations of related variables. Applications range from identifying diseases from symptoms to class…