2 citations · 2 across the 5 of their papers we have counts for
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Efficient classical computation of the neural tangent kernel of quantum neural networks
Anderson Melchor Hernandez, Davide Pastorello, Giacomo De Palma
We propose an efficient classical algorithm to estimate the Neural Tangent Kernel (NTK) associated with a broad class of quantum neural networks. These networks consist of arbitrar…
A large multi-agent system with noise both in position and control
Giuseppe D'Onofrio, Anderson Melchor Hernandez
In this work, we consider a multi-population system where the dynamics of each agent evolve according to a system of stochastic differential equations in a general functional setup…
Mean-field limit from general mixtures of experts to quantum neural networks
Anderson Melchor Hernandez, Davide Pastorello, Giacomo De Palma
In this work, we study the asymptotic behavior of Mixture of Experts (MoE) trained via gradient flow on supervised learning problems. Our main result establishes the propagation of…