15 citations · 41 across the 11 of their papers we have counts for
5 papers · 1 filter
Hybrid Quantum Neural Networks: Theory, Implementations, and Applications
Léo Monbroussou, Maniraman Periyasamy, Viacheslav Kuzmin +4
Artificial intelligence has been transformed by deep neural networks, yet the search for new learning architectures continues. Quantum machine learning offers one such direction, a…
Classical simulation and model concentration in passive linear optics
Léo Monbroussou, Hugo Thomas, Hela Mhiri +2
Passive linear optics is a restricted model of quantum computation, with complexity-theoretic evidence of quantum advantage for sampling tasks and low losses that make it attractiv…
Scalable Message-Passing Quantum Graph Neural Networks in the Weisfeiler-Leman Hierarchy
Snehal Raj, Brian Coyle, Léo Monbroussou +3
Graphs provide a natural language for relational data in chemistry, biology and optimisation. Graph neural networks (GNNs) have driven much of the recent progress in learning from…
Quantum Machine Learning for Industrial Applications
Léo Monbroussou
Recent advances in Machine Learning have transformed numerous industrial sectors, yet classical paradigms face fundamental limitations: rapidly growing data volumes, rising computa…
Boson sampling beyond the dilute regime: second moments and anti-concentration
Hela Mhiri, Hugo Thomas, Léo Monbroussou +3
Boson sampling is a leading candidate for demonstrating quantum advantage in photonic systems. Despite significant experimental and theoretical progress, a characterization of its…