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John Pearson

4 accepted papers

2026

Dynamic Compression Flows for Neuroscience Data

ICML 2026poster

While neuroscience experiments have repeatedly demonstrated the involvement of large populations of neurons in even simple behaviors, these studies have just as often reported that the collective dynamics of neural activity are approximately low-dimensional. As a result, methods for identifying low-…

Cited by 0SourceScholar
2024

Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models

NeurIPS 2024poster

Beyond estimating parameters of interest from data, one of the key goals of statistical inference is to properly quantify uncertainty in these estimates. In Bayesian inference, this uncertainty is provided by the posterior distribution, the computation of which typically involves an intractable high…

2022

Efficient coding, channel capacity, and the emergence of retinal mosaics

NeurIPS 2022accept

Among the most striking features of retinal organization is the grouping of its output neurons, the retinal ganglion cells (RGCs), into a diversity of functional types. Each of these types exhibits a mosaic-like organization of receptive fields (RFs) that tiles the retina and visual space. Previous…

Cited by 17SourcePDFScholar
2021

Bubblewrap: Online tiling and real-time flow prediction on neural manifolds

NeurIPS 2021poster

While most classic studies of function in experimental neuroscience have focused on the coding properties of individual neurons, recent developments in recording technologies have resulted in an increasing emphasis on the dynamics of neural populations. This has given rise to a wide variety of model…