4 citations · 8 across the 5 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
quant-ph2025
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…
math-ph2025
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…