5 papers
On the Stability of the Jacobian Matrix in Deep Neural Networks
Benjamin Dadoun, Soufiane Hayou, Hanan Salam +2
Deep neural networks are known to suffer from exploding or vanishing gradients as depth increases, a phenomenon closely tied to the spectral behavior of the input-output Jacobian.…
Monotonicity of the logarithmic energy for random matrices
Djalil Chafaï, Benjamin Dadoun, Pierre Youssef
It is well-known that the semi-circle law, which is the limiting distribution in the Wigner theorem, is the minimizer of the logarithmic energy penalized by the second moment. A ve…
Maximal correlation and monotonicity of free entropy and Stein discrepancy
Benjamin Dadoun, Pierre Youssef
We introduce the maximal correlation coefficient between two noncommutative probability subspaces and and show that the maximal correlation coefficient bet…
Self-similar growth-fragmentations as scaling limits of Markov branching processes
Benjamin Dadoun
We provide explicit conditions, in terms of the transition kernel of its driving particle, for a Markov branching process to admit a scaling limit toward a self-similar growth-frag…
Asymptotics of self-similar growth-fragmentation processes
Benjamin Dadoun
Markovian growth-fragmentation processes introduced by Bertoin extend the pure fragmentation model by allowing the fragments to grow larger or smaller between dislocation events. W…