2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Enhancing Neural Training via a Correlated Dynamics Model
Jonathan Brokman, Roy Betser, Rotem Turjeman +3
As neural networks grow in scale, their training becomes both computationally demanding and rich in dynamics. Amidst the flourishing interest in these training dynamics, we present…
cs.LG2022★ 1 cited
The Underlying Correlated Dynamics in Neural Training
Rotem Turjeman, Tom Berkov, Ido Cohen +1
Training of neural networks is a computationally intensive task. The significance of understanding and modeling the training dynamics is growing as increasingly larger networks are…
math.AP2021★ 2 cited
Total-Variation -- Fast Gradient Flow and Relations to Koopman Theory
Ido Cohen, Tom Berkov, Guy Gilboa
The space-discrete Total Variation (TV) flow is analyzed using several mode decomposition techniques. In the one-dimensional case, we provide analytic formulations to Dynamic Mode…