Author

Xiaolin Hu

State Key Laboratory of Intelligent Technology and SystemsORCID 0000-0002-4907-7354Unclaimed ORCID profile · follow to get notified of new preprints

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Xiaolin Hu1 paper

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Neuroscience· 2

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Approach:statistical model· 2 Approach:deep learning· 1 Organism:human· 1

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Alexander MaÿeiD· 1 shared Andreas Karl EngeliD· 1 shared Fangzhou LiaoiD· 1 shared Jonathan DaumeiD· 1 shared Peng WangiD· 1 shared Sen SongiD· 1 shared

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2018-2019 · peak 1/yr

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6 top collaborators · 7 mutual co-author links

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1 shared paperNeuroscience

Alexander MaÿeORCID

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2 papers

Recent·Most cited

NeuroscienceFrontiers in Integrative NeurosciencePeer-reviewedAug 20, 2019

An oscillator ensemble model of sequence learning

Alexander Maÿe, Peng Wang, Jonathan Daume…·Andreas Karl Engel

The paper develops a computational model of sequence learning using neural oscillators and compares it to human behavioral results, showing good agreement in error rates across sequence complexities.

2 citations

humanstatistical model

𝕏 PostBluesky

NeurosciencebioRxivPreprintJan 7, 2018

Emergence of V1 connectivity pattern and Hebbian rule in a performance-optimized artificial neural network

Fangzhou Liao, Xiaolin Hu, Sen Song

This study shows that adding recurrent connections to a CNN mimics V1 connectivity patterns and Hebbian rule, suggesting deep learning can model biological neural networks.

DOI 10.1101/244350

deep learningstatistical model

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