2 papers
cs.LG2025
Gradient Flow Equations for Deep Linear Neural Networks: A Survey from a Network Perspective
Joel Wendin, Claudio Altafini
The paper surveys recent progresses in understanding the dynamics and loss landscape of the gradient flow equations associated to deep linear neural networks, i.e., the gradient de…
cs.LG2025
Computing frustration and near-monotonicity in deep neural networks
Joel Wendin, Erik G. Larsson, Claudio Altafini
For the signed graph associated to a deep neural network, one can compute the frustration level, i.e., test how close or distant the graph is to structural balance. For all the pre…