What Makes Data Suitable for a Locally Connected Neural Network? A Necessary and Sufficient Condition Based on Quantum Entanglement. - Yotam Alexander; Nimrod De La Vega; Noam Razin; Nadav Cohen 001 (NeurIPS, 2023)

Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States. - Noam Razin; Yotam Alexander; Edo Cohen-Karlik; Raja Giryes; Amir Globerson; Nadav Cohen 001 (ICML, 2024)

The Implicit Bias of Structured State Space Models Can Be Poisoned With Clean Labels. - Yonatan Slutzky; Yotam Alexander; Noam Razin; Nadav Cohen 001 (CoRR, 2024)

Revisiting Glorot Initialization for Long-Range Linear Recurrences. - Noga Bar; Mariia Seleznova; Yotam Alexander; Gitta Kutyniok; Raja Giryes (CoRR, 2025)

Do Neural Networks Need Gradient Descent to Generalize? A Theoretical Study. - Yotam Alexander; Yonatan Slutzky; Yuval Ran-Milo; Nadav Cohen 001 (CoRR, 2025)