Stebėti
Simon C Marshall
Simon C Marshall
PhD candidate, Universiteit Leiden
Patvirtintas el. paštas liacs.leidenuniv.nl
Pavadinimas
Cituota
Cituota
Metai
Parametrized quantum policies for reinforcement learning
S Jerbi, C Gyurik, S Marshall, H Briegel, V Dunjko
Advances in Neural Information Processing Systems 34, 28362-28375, 2021
1732021
Shadows of quantum machine learning
S Jerbi, C Gyurik, SC Marshall, R Molteni, V Dunjko
Nature Communications 15 (1), 5676, 2024
422024
High dimensional quantum machine learning with small quantum computers
SC Marshall, C Gyurik, V Dunjko
Quantum 7, 1078, 2023
282023
Understanding polysemanticity in neural networks through coding theory
SC Marshall, JH Kirchner
arXiv preprint arXiv:2401.17975, 2024
52024
High dimensional quantum learning with small quantum computers
SC Marshall, C Gyurik, V Dunjko
arXiv preprint arXiv:2203.13739, 2022
32022
Improved separation between quantum and classical computers for sampling and functional tasks
SC Marshall, S Aaronson, V Dunjko
arXiv preprint arXiv:2410.20935, 2024
22024
PDQMA= DQMA= NEXP: QMA With Hidden Variables and Non-collapsing Measurements
S Aaronson, S Grewal, V Iyer, SC Marshall, R Ramachandran
arXiv preprint arXiv:2403.02543, 2024
22024
All this for one qubit? Bounds on local circuit cutting schemes
SC Marshall, J Tura, V Dunjko
arXiv preprint arXiv:2303.13422, 2023
22023
On Bounded Advice Classes
S Marshall, C Gyurik, V Dunjko
arXiv preprint arXiv:2405.18155, 2024
12024
Understanding polysemanticity and improved interpretability in neural networks through coding theory
SC Marshall, JH Kirchner
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Straipsniai 1–10