1.5k citations
- University of OxfordGB29 papers
- Harvard UniversityUS4 papers
- Science OxfordGB4 papers
- University of California, BerkeleyUS3 papers
- University of CambridgeGB3 papers
- University of ManchesterGB3 papers
- Vrije Universiteit AmsterdamNL3 papers
- Wellcome Sanger InstituteGB3 papers
- Athens University of Economics and BusinessGR2 papers
- Broad InstituteUS2 papers
- Carnegie Mellon UniversityUS2 papers
- Centre National de la Recherche ScientifiqueFR2 papers
7 papers · 1 filter
Efficient convergence through adaptive learning in sequential Monte Carlo Expectation Maximization
Donna Henderson, Gerton Lunter
Expectation maximization (EM) is a technique for estimating maximum-likelihood parameters of a latent variable model given observed data by alternating between taking expectations…
Latent variable model selection for Gaussian conditional random fields
Benjamin Frot, Luke Jostins, Gil McVean
We consider the problem of learning a conditional Gaussian graphical model in the presence of latent variables. Building on recent advances in this field, we suggest a method that…
The Hamming Ball Sampler
Michalis K. Titsias, Christopher Yau
We introduce the Hamming Ball Sampler, a novel Markov Chain Monte Carlo algorithm, for efficient inference in statistical models involving high-dimensional discrete state spaces. T…
Network inference in matrix-variate Gaussian models with non-independent noise
Andy Dahl, Victoria Hore, Valentina Iotchkova +1
Inferring a graphical model or network from observational data from a large number of variables is a well studied problem in machine learning and computational statistics. In this…
Meta-Analysis of Gene Level Association Tests
Dajiang J. Liu, Gina M. Peloso, Xiaowei Zhan +18
The vast majority of connections between complex disease and common genetic variants were identified through meta-analysis, a powerful approach that enables large samples sizes whi…
Replication in Genome-Wide Association Studies
Peter Kraft, Eleftheria Zeggini, John P. A. Ioannidis
Replication helps ensure that a genotype-phenotype association observed in a genome-wide association (GWA) study represents a credible association and is not a chance finding or an…