Author

Catherine D. Schuman

University of Tennessee at KnoxvilleORCID 0000-0002-4264-8097Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 1

Signature Assays, Organisms & Methods

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Organism:C. elegans· 1 Approach:statistical model· 1

Frequent Co-Authors

Maryam ParsaiD· 1 shared Samuel SchmidgalliD· 1 shared

Activity by Year

2022-2022 · peak 1/yr

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2 top collaborators · 1 mutual co-author link

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1 shared paperNeuroscience

Maryam ParsaORCID

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1 paper

Recent·Most cited

Biological connectomes as a representation for the architecture of artificial neural networks

Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa

The paper explores how biological connectomes can inform artificial neural network design, showing that architectural statistics from biological circuits provide a useful prior for machine learning tasks.

bioRxiv · Sep 30, 2022 · PreprintNeuroscience