Author

Liam Paninski

Columbia UniversityORCID 0000-0002-0276-7032Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 57 Bioinformatics· 3 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 28 Organism:mouse· 26 Assay:imaging· 25 Assay:electronic health records· 23 Research Focus:cell type annotation· 17 Approach:experimental assay· 17 Research Focus:benchmarking· 14 Research Focus:clustering· 11

Frequent Co-Authors

Cole HurwitziD· 10 shared Matthew R WhitewayiD· 10 shared Erdem VaroliD· 9 shared Julien BoussardiD· 9 shared Anne K. ChurchlandiD· 8 shared Ian Kinsella· 8 shared E. Kelly BuchananiD· 7 shared Jean‐Paul NoeliD· 7 shared

Activity by Year

2016-2026 · peak 10/yr

Co-Author Collaboration Network

10 top collaborators · 34 mutual co-author links

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10 shared papersNeuroscience

Cole HurwitzORCID

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61 papers

Recent·Most cited

BioinformaticsbioRxivPreprintNov 19, 2016

Scalable variational inference for super resolution microscopy

Ruoxi Sun, Evan Archer, Liam Paninski

This paper develops Bayesian image processing methods for super-resolution microscopy that improve resolution while maintaining computational efficiency.

6 citations

imagingvariational autoencoder

𝕏 PostBluesky