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cs.LG2024
Hidden Activations Are Not Enough: A General Approach to Neural Network Predictions
Samuel Leblanc, Aiky Rasolomanana, Marco Armenta
We introduce a novel mathematical framework for analyzing neural networks using tools from quiver representation theory. This framework enables us to quantify the similarity betwee…
quant-ph2024★ 1 cited
Fermionic Machine Learning
Jérémie Gince, Jean-Michel Pagé, Marco Armenta +2
We introduce fermionic machine learning (FermiML), a machine learning framework based on fermionic quantum computation. FermiML models are expressed in terms of parameterized match…