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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…
Noise-robust ground state energy estimates from deep quantum circuits
Harish J. Vallury, Michael A. Jones, Gregory A. L. White +3
In the lead up to fault tolerance, the utility of quantum computing will be determined by how adequately the effects of noise can be circumvented in quantum algorithms. Hybrid quan…
A kernel-based quantum random forest for improved classification
Maiyuren Srikumar, Charles D. Hill, Lloyd C. L. Hollenberg
The emergence of Quantum Machine Learning (QML) to enhance traditional classical learning methods has seen various limitations to its realisation. There is therefore an imperative…
Automated Quantum Circuit Design with Nested Monte Carlo Tree Search
Pei-Yong Wang, Muhammad Usman, Udaya Parampalli +2
Quantum algorithms based on variational approaches are one of the most promising methods to construct quantum solutions and have found a myriad of applications in the last few year…