no code implementations • 13 Feb 2024 • Joachim Bona-Pellissier, Fran çois Malgouyres, Fran çois Bachoc
When the inputs are fixed, we prove that the dimension of this set changes and that the local dimension, called batch functional dimension, is almost surely determined by the activation patterns in the hidden layers.
no code implementations • 15 Jun 2022 • Joachim Bona-Pellissier, François Malgouyres, François Bachoc
Is a sample rich enough to determine, at least locally, the parameters of a neural network?
no code implementations • 24 Dec 2021 • Joachim Bona-Pellissier, François Bachoc, François Malgouyres
The possibility for one to recover the parameters-weights and biases-of a neural network thanks to the knowledge of its function on a subset of the input space can be, depending on the situation, a curse or a blessing.
