57 citations · 59 across the 4 of their papers we have counts for
4 papers
Differentiable Weightless Neural Networks
Alan T. L. Bacellar, Zachary Susskind, Mauricio Breternitz +4
We introduce the Differentiable Weightless Neural Network (DWN), a model based on interconnected lookup tables. Training of DWNs is enabled by a novel Extended Finite Difference te…
Weightless Neural Networks for Efficient Edge Inference
Zachary Susskind, Aman Arora, Igor Dantas Dos Santos Miranda +8
Weightless Neural Networks (WNNs) are a class of machine learning model which use table lookups to perform inference. This is in contrast with Deep Neural Networks (DNNs), which us…
Efficiency and Scalability of Multi-Lane Capsule Networks (MLCN)
Vanderson M. do Rosario, Mauricio Breternitz, Edson Borin
Some Deep Neural Networks (DNN) have what we call lanes, or they can be reorganized as such. Lanes are paths in the network which are data-independent and typically learn different…
The Multi-Lane Capsule Network (MLCN)
Vanderson Martins do Rosario, Edson Borin, Mauricio Breternitz
We introduce Multi-Lane Capsule Networks (MLCN), which are a separable and resource efficient organization of Capsule Networks (CapsNet) that allows parallel processing, while achi…