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20132021
most citedKernel methods on spike train space for neuroscience: a tutorial

61 citations · 84 across the 8 of their papers we have counts for

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6 papers · 1 filter

stat.ML2017

Model Criticism in Latent Space

Sohan Seth, Iain Murray, Christopher K. I. Williams

Model criticism is usually carried out by assessing if replicated data generated under the fitted model looks similar to the observed data, see e.g. Gelman, Carlin, Stern, and Rubi…

stat.ML2015★ 16 cited

Modelling-based experiment retrieval: A case study with gene expression clustering

Paul Blomstedt, Ritabrata Dutta, Sohan Seth +2

Motivation: Public and private repositories of experimental data are growing to sizes that require dedicated methods for finding relevant data. To improve on the state of the art o…

stat.ML2014

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood

Sohan Seth, John Shawe-Taylor, Samuel Kaski

We study the task of retrieving relevant experiments given a query experiment. By experiment, we mean a collection of measurements from a set of `covariates' and the associated `ou…

stat.ML2013★ 5 cited

Probabilistic Archetypal Analysis

Sohan Seth, Manuel J. A. Eugster

Archetypal analysis represents a set of observations as convex combinations of pure patterns, or archetypes. The original geometric formulation of finding archetypes by approximati…

stat.ML2013

Bayesian Extensions of Kernel Least Mean Squares

Il Memming Park, Sohan Seth, Steven Van Vaerenbergh

The kernel least mean squares (KLMS) algorithm is a computationally efficient nonlinear adaptive filtering method that "kernelizes" the celebrated (linear) least mean squares algor…

stat.ML2013★ 2 cited

Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space

Ritabrata Dutta, Sohan Seth, Samuel Kaski

We address the problem of retrieving relevant experiments given a query experiment, motivated by the public databases of datasets in molecular biology and other experimental scienc…