7 citations · 18 across the 9 of their papers we have counts for
3 papers · 1 filter
Provable Benefits of Complex Parameterizations for Structured State Space Models
Yuval Ran-Milo, Eden Lumbroso, Edo Cohen-Karlik +3
Structured state space models (SSMs), the core engine behind prominent neural networks such as S4 and Mamba, are linear dynamical systems adhering to a specified structure, most no…
Overcoming Order in Autoregressive Graph Generation
Edo Cohen-Karlik, Eyal Rozenberg, Daniel Freedman
Graph generation is a fundamental problem in various domains, including chemistry and social networks. Recent work has shown that molecular graph generation using recurrent neural…
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
Noam Razin, Yotam Alexander, Edo Cohen-Karlik +3
In modern machine learning, models can often fit training data in numerous ways, some of which perform well on unseen (test) data, while others do not. Remarkably, in such cases gr…