380 citations · 1.1k across the 43 of their papers we have counts for
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Automated scalable segmentation of neurons from multispectral images
Uygar Sümbül, Douglas Roussien, Fei Chen +5
Reconstruction of neuroanatomy is a fundamental problem in neuroscience. Stochastic expression of colors in individual cells is a promising tool, although its use in the nervous sy…
Linear dynamical neural population models through nonlinear embeddings
Yuanjun Gao, Evan Archer, Liam Paninski +1
A body of recent work in modeling neural activity focuses on recovering low-dimensional latent features that capture the statistical structure of large-scale neural populations. Mo…
Bayesian Learning of Kernel Embeddings
Seth Flaxman, Dino Sejdinovic, John P. Cunningham +1
Kernel methods are one of the mainstays of machine learning, but the problem of kernel learning remains challenging, with only a few heuristics and very little theory. This is of p…
Preconditioning Kernel Matrices
Kurt Cutajar, Michael A. Osborne, John P. Cunningham +1
The computational and storage complexity of kernel machines presents the primary barrier to their scaling to large, modern, datasets. A common way to tackle the scalability issue i…