Search Results for author: Sohan Seth

Found 9 papers, 1 papers with code

Census-Independent Population Estimation using Representation Learning

no code implementations6 Oct 2021 Isaac Neal, Sohan Seth, Gary Watmough, Mamadou S. Diallo

Knowledge of population distribution is critical for building infrastructure, distributing resources, and monitoring the progress of sustainable development goals.

Representation Learning

Towards Sustainable Census Independent Population Estimation in Mozambique

no code implementations26 Apr 2021 Isaac Neal, Sohan Seth, Gary Watmough, Mamadou Saliou Diallo

Reliable and frequent population estimation is key for making policies around vaccination and planning infrastructure delivery.

Transfer Learning

Model Criticism in Latent Space

1 code implementation13 Nov 2017 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 Rubin [2004, p. 165].

Gaussian Processes

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

no code implementations19 May 2015 Paul Blomstedt, Ritabrata Dutta, Sohan Seth, Alvis Brazma, Samuel Kaski

For retrieval of gene expression experiments, we use a probabilistic model called product partition model, which induces a clustering of genes that show similar expression patterns across a number of samples.

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood

no code implementations19 Feb 2014 Sohan Seth, John Shawe-Taylor, Samuel Kaski

To incorporate this information in the retrieval task, we suggest employing a retrieval metric that utilizes probabilistic models learned from the measurements.

Probabilistic Archetypal Analysis

no code implementations29 Dec 2013 Sohan Seth, Manuel J. A. Eugster

Archetypal analysis represents a set of observations as convex combinations of pure patterns, or archetypes.

Bayesian Extensions of Kernel Least Mean Squares

no code implementations20 Oct 2013 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 algorithm.

Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space

no code implementations8 Oct 2013 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 sciences, and the need of scientists to relate to earlier work on the level of actual measurement data.

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