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On sequential construction of binary neural networks

IEEE Transactions on Neural Networks, 1995
A new technique called sequential window learning (SWL), for the construction of two-layer perceptrons with binary inputs is presented. It generates the number of hidden neurons together with the correct values for the weights, starting from any binary training set.
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Binary Neural Networks for FPGAs

This report investigates the feasibility of implementing Binary Neural Networks (BNNs) for real-time tau identification in the ATLAS Level-0 trigger, in the context of the ATLAS Phase-II Upgrade and the Next Generation Global Trigger project. BNNs, which operate with binary weights and activations, offer a promising solution by drastically reducing ...
Mastoreka, Maria +3 more
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Binary Neural Network

2022
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Machine-learning-assisted design of a binary descriptor to decipher electronic and structural effects on sulfur reduction kinetics

Nature Catalysis, 2023
Tianshuai Wang, Tao Shengyu
exaly

XNOR-RRAM: A scalable and parallel resistive synaptic architecture for binary neural networks