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Stephen L Keeley

2 accepted papers

2025

Scalable inference of functional neural connectivity at submillisecond timescales

NeurIPS 2025poster

The Poisson Generalized Linear Model (GLM) is a foundational tool for analyzing neural spike train data. However, standard implementations rely on discretizing spike times into binned count data, limiting temporal resolution and scalability. Here, we develop stochastic optimization methods and polyn…

Cited by 1SourceScholar
2024

Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data

ICLR 2024poster

Characterizing the relationship between neural population activity and behavioral data is a central goal of neuroscience. While latent variable models (LVMs) are successful in describing high-dimensional data, they are typically only designed for a single type of data, making it difficult to identif…

Cited by 11SourcePDFScholar