15 citations · 41 across the 11 of their papers we have counts for
4 papers · 1 filter
When Quantum and Classical Models Disagree: Learning Beyond Minimum Norm Least Square
Slimane Thabet, Léo Monbroussou, Eliott Z. Mamon +1
Quantum Machine Learning algorithms based on Variational Quantum Circuits (VQCs) are important candidates for useful application of quantum computing. It is known that a VQC is a l…
Towards quantum advantage with photonic state injection
Léo Monbroussou, Eliott Z. Mamon, Hugo Thomas +3
We propose a new scheme for near-term photonic quantum device that allows to increase the expressive power of the quantum models beyond what linear optics can do. This scheme relie…
Subspace Preserving Quantum Convolutional Neural Network Architectures
Léo Monbroussou, Jonas Landman, Letao Wang +2
Subspace preserving quantum circuits are a class of quantum algorithms that, relying on some symmetries in the computation, can offer theoretical guarantees for their training. Tho…
Constrained and Vanishing Expressivity of Quantum Fourier Models
Hela Mhiri, Leo Monbroussou, Mario Herrero-Gonzalez +3
In this work, we highlight an unforeseen behavior of the expressivity of Parameterized Quantum Circuits (PQCs) for machine learning. A large class of these models, seen as Fourier…