[HTML][HTML] Deep physical neural networks trained with backpropagation
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability. Deep-learning …
their energy requirements now increasingly limit their scalability. Deep-learning …
Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - …, 2022 - pubmed.ncbi.nlm.nih.gov
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability 1. Deep-learning …
their energy requirements now increasingly limit their scalability 1. Deep-learning …
Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - econpapers.repec.org
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability1. Deep-learning …
their energy requirements now increasingly limit their scalability1. Deep-learning …
[PDF][PDF] Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - dil.umbc.edu
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability 1. Deep-learning …
their energy requirements now increasingly limit their scalability 1. Deep-learning …
Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - par.nsf.gov
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability 1. Deep-learning …
their energy requirements now increasingly limit their scalability 1. Deep-learning …
[HTML][HTML] Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - ncbi.nlm.nih.gov
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability 1. Deep-learning …
their energy requirements now increasingly limit their scalability 1. Deep-learning …
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems
LG Wright, T Onodera, MM Stein, T Wang… - arXiv preprint arXiv …, 2021 - arxiv.org
Deep neural networks have become a pervasive tool in science and engineering. However,
modern deep neural networks' growing energy requirements now increasingly limit their …
modern deep neural networks' growing energy requirements now increasingly limit their …
Deep physical neural networks enabled by a backpropagation algorithm for arbitrary physical systems
LG Wright, T Onodera, MM Stein, T Wang… - arXiv e …, 2021 - ui.adsabs.harvard.edu
Deep neural networks have become a pervasive tool in science and engineering. However,
modern deep neural networks' growing energy requirements now increasingly limit their …
modern deep neural networks' growing energy requirements now increasingly limit their …
Deep physical neural networks trained with backpropagation
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - open.bu.edu
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability1. Deep-learning …
their energy requirements now increasingly limit their scalability1. Deep-learning …
Deep physical neural networks trained with backpropagation.
LG Wright, T Onodera, MM Stein, T Wang… - Nature, 2022 - europepmc.org
Deep-learning models have become pervasive tools in science and engineering. However,
their energy requirements now increasingly limit their scalability 1. Deep-learning …
their energy requirements now increasingly limit their scalability 1. Deep-learning …