210 citations · 984 across the 29 of their papers we have counts for
5 papers · 1 filter
Inductive Bias of Deep Convolutional Networks through Pooling Geometry
Nadav Cohen, Amnon Shashua
Our formal understanding of the inductive bias that drives the success of convolutional networks on computer vision tasks is limited. In particular, it is unclear what makes hypoth…
Convolutional Rectifier Networks as Generalized Tensor Decompositions
Nadav Cohen, Amnon Shashua
Convolutional rectifier networks, i.e. convolutional neural networks with rectified linear activation and max or average pooling, are the cornerstone of modern deep learning. Howev…
On the Expressive Power of Deep Learning: A Tensor Analysis
Nadav Cohen, Or Sharir, Amnon Shashua
It has long been conjectured that hypotheses spaces suitable for data that is compositional in nature, such as text or images, may be more efficiently represented with deep hierarc…
Deep SimNets
Nadav Cohen, Or Sharir, Amnon Shashua
We present a deep layered architecture that generalizes convolutional neural networks (ConvNets). The architecture, called SimNets, is driven by two operators: (i) a similarity fun…
SimNets: A Generalization of Convolutional Networks
Nadav Cohen, Amnon Shashua
We present a deep layered architecture that generalizes classical convolutional neural networks (ConvNets). The architecture, called SimNets, is driven by two operators, one being…