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Vinam Arora

3 accepted papers

2025

Know Thyself by Knowing Others: Learning Neuron Identity from Population Context

NeurIPS 2025poster

Identifying the functional identity of individual neurons is essential for interpreting circuit dynamics, yet it remains a major challenge in large-scale _in vivo_ recordings where anatomical and molecular labels are often unavailable. Here we introduce NuCLR, a self-supervised framework that learns…

Cited by 0SourcecodeScholar
2025

Multi-session, multi-task neural decoding from distinct cell-types and brain regions

ICLR 2025spotlight

Recent work has shown that scale is important for improved brain decoding, with more data leading to greater decoding accuracy. However, large-scale decoding across many different datasets is challenging because neural circuits are heterogeneous---each brain region contains a unique mix of cellular…

Cited by 1SourcePDFScholar
2023

A Unified, Scalable Framework for Neural Population Decoding

NeurIPS 2023poster

Our ability to use deep learning approaches to decipher neural activity would likely benefit from greater scale, in terms of both the model size and the datasets. However, the integration of many neural recordings into one unified model is challenging, as each recording contains the activity of diff…

Cited by 41SourcePDFScholar