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      Replica symmetry breaking in bipartite spin glasses and neural networks

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      Physical Review E

      American Physical Society (APS)

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          Most cited references 37

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          Deep learning.

          Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.
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            Solvable Model of a Spin-Glass

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              Stability of the Sherrington-Kirkpatrick solution of a spin glass model

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                Author and article information

                Journal
                PLEEE8
                Physical Review E
                Phys. Rev. E
                American Physical Society (APS)
                2470-0045
                2470-0053
                August 2018
                August 15 2018
                : 98
                : 2
                Article
                10.1103/PhysRevE.98.022116
                © 2018

                https://link.aps.org/licenses/aps-default-license

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