109 citations · 395 across the 8 of their papers we have counts for
9 papers
Provably Trainable Rotationally Equivariant Quantum Machine Learning
Maxwell T. West, Jamie Heredge, Martin Sevior +1
Exploiting the power of quantum computation to realise superior machine learning algorithmshas been a major research focus of recent years, but the prospects of quantum machine lea…
Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning
Maxwell T. West, Azar C. Nakhl, Jamie Heredge +4
Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realisation for practical applications re…
Towards quantum enhanced adversarial robustness in machine learning
Maxwell T. West, Shu-Lok Tsang, Jia S. Low +5
Machine learning algorithms are powerful tools for data driven tasks such as image classification and feature detection, however their vulnerability to adversarial examples - input…
Boosted Ensembles of Qubit and Continuous Variable Quantum Support Vector Machines for B Meson Flavour Tagging
Maxwell T. West, Martin Sevior, Muhammad Usman
The recent physical realisation of quantum computers with dozens to hundreds of noisy qubits has given birth to an intense search for useful applications of their unique capabiliti…
Hybrid Quantum-Classical Generative Adversarial Network for High Resolution Image Generation
Shu Lok Tsang, Maxwell T. West, Sarah M. Erfani +1
Quantum machine learning (QML) has received increasing attention due to its potential to outperform classical machine learning methods in problems pertaining classification and ide…
Reflection Equivariant Quantum Neural Networks for Enhanced Image Classification
Maxwell T. West, Martin Sevior, Muhammad Usman
Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding…
Benchmarking Adversarially Robust Quantum Machine Learning at Scale
Maxwell T. West, Sarah M. Erfani, Christopher Leckie +3
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology and industry. Despite their accuracy and sophisticati…
Quantum Computing: A Taxonomy, Systematic Review and Future Directions
Sukhpal Singh Gill, Adarsh Kumar, Harvinder Singh +4
Quantum computing is an emerging paradigm with the potential to offer significant computational advantage over conventional classical computing by exploiting quantum-mechanical pri…
Valley filtering and spatial maps of coupling between silicon donors and quantum dots
J. Salfi, B. Voisin, A. Tankasala +6
Exchange coupling is a key ingredient for spin-based quantum technologies since it can be used to entangle spin qubits and create logical spin qubits. However, the influence of the…