3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2023
2-D SSM: A General Spatial Layer for Visual Transformers
Ethan Baron, Itamar Zimerman, Lior Wolf
A central objective in computer vision is to design models with appropriate 2-D inductive bias. Desiderata for 2D inductive bias include two-dimensional position awareness, dynamic…
cs.LG2023★ 3 cited
Decision S4: Efficient Sequence-Based RL via State Spaces Layers
Shmuel Bar-David, Itamar Zimerman, Eliya Nachmani +1
Recently, sequence learning methods have been applied to the problem of off-policy Reinforcement Learning, including the seminal work on Decision Transformers, which employs transf…
cs.LG2023
Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption
Moran Baruch, Nir Drucker, Gilad Ezov +5
Training large-scale CNNs that during inference can be run under Homomorphic Encryption (HE) is challenging due to the need to use only polynomial operations. This limits HE-based…