Author

pietro zamberlan

Institut de la Vision

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Neuroscience· 1

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Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Organism:mouse· 1 Approach:transformer / foundation model· 1 Organism:zebrafish· 1

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Arno OnkeniD· 1 shared Matteo FarinaiD· 1 shared Ulisse FerrariiD· 1 shared

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2026-2026 · peak 1/yr

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Arno OnkenORCID

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1 paper

Recent·Most cited

Biologically grounded locality priors close the data gap for vision transformers in neural prediction

Matteo Farina, pietro zamberlan, Arno Onken, Ulisse Ferrari

The paper introduces CiRF-ViT, a vision transformer with per-neuron locality priors, achieving high performance in small-scale neural prediction tasks.

bioRxiv · Sep 8, 2026 · PreprintNeuroscience