Now showing items 1674-1693 of 204997

    • Bayesian generalised ensemble Markov chain Monte Carlo 

      Frellsen, Jes; Winther, Ole; Ghahramani, Zoubin; Ferkinghoff-Borg, Jesper (Microtome Publishing, 2016)
      Bayesian generalised ensemble (BayesGE) is a new method that addresses two major drawbacks of standard Markov chain Monte Carlo algorithms for inference in high-dimensional probability models: inapplicability to estimate ...
    • Bayesian Inference of Accurate Population Sizes and FRET Efficiencies from Single Diffusing Biomolecules 

      Murphy, Rebecca R.; Danezis, George; Horrocks, Mathew H.; Jackson, Sophie E.; Klenerman, David (ACS, 2014-08-08)
      It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in ...
    • Bayesian Learning For The Type-3 Joint Sparse Signal Recovery 

      Chen, Wei; Wassell, Ian J. (IEEE, 2016)
      Compressed sensing (CS) is a signal acquisition paradigm that utilises the finding that a small number of linear projections of a sparse signal have enough information for stable recovery. This paper develops a Bayesian ...
    • A Bayesian method for microseismic source inversion 

      Pugh, D. J.; White, R. S.; Christie, P. A. F. (Oxford University Press, 2016-05-18)
      Earthquake source inversion is highly dependent on location determination and velocity models. Uncertainties in both the model parameters and the observations need to be rigorously incorporated into an inversion approach. ...
    • Bayesian methods for gravitational waves and neural networks 

      Graff, Philip B. (2012-10-09)
      Einstein’s general theory of relativity has withstood 100 years of testing and will soon be facing one of its toughest challenges. In a few years we expect to be entering the era of the first direct observations of ...
    • Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables 

      Thompson, Simon G.; Burgess, Stephen (Wiley, 2010-03-08)
      Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the ...
    • Bayesian methods in music modelling 

      Peeling, Paul (2011-03-15)
      This thesis presents several hierarchical generative Bayesian models of musical signals designed to improve the accuracy of existing multiple pitch detection systems and other musical signal processing applications whilst ...
    • Bayesian Model Choice in Cumulative Link Ordinal Regression Models 

      McKinley, Trevelyan; Morters, Michelle; Wood, James L. N. (International Society for Bayesian Analysis, 2015-01-28)
      The use of the proportional odds (PO) model for ordinal regression is ubiquitous in the literature. If the assumption of parallel lines does not hold for the data, then an alternative is to specify a non-proportional odds ...
    • Bayesian regularization of the length of memory in reversible sequences 

      Bacallado, Sergio; Pande, Vijay; Favaro, Stefano; Trippa, Lorenzo (Wiley, 2015-10-16)
      Variable order Markov chains have been used to model discrete sequential data in a variety of fields. A host of methods exist to estimate the history-dependent lengths of memory which characterize these models and to predict ...
    • Bayesian source inversion of microseismic events 

      Pugh, David James (2016-01-05)
      Rapid stress release at the source of an earthquake produces seismic waves. Observations of the particle motions from such waves are used in source inversion to characterise the dynamic behaviour of the source and to help ...
    • Bayesian Structured Prediction using Gaussian Processes 

      Bratières, Sébastien; Quadrianto, Novi; Ghahramani, Zoubin (IEEE, 2014-10-31)
      We introduce a conceptually novel structured prediction model, GPstruct, which is kernelized, non-parametric and Bayesian, by design. We motivate the model with respect to existing approaches, among others, conditional ...
    • BayesPeak: Bayesian analysis of ChIP-seq data 

      Spyrou, Christiana; Stark, Rory; Lynch, Andy G; Tavaré, Simon (2009-09-21)
      Abstract Background High-throughput sequencing technology has become popular and widely used to study protein and DNA interactions. Chromatin immunoprecipitation, followed by sequencing of the resulting samples, produces ...
    • baySeq: Empirical Bayesian Methods For Identifying Differential Expression In Sequence Count Data 

      Hardcastle, Thomas; Kelly, Krystyna A (2010-08-10)
      Abstract Background High throughput sequencing has become an important technology for studying expression levels in many types of genomic, and particularly transcriptomic, data. One key way of analysing such data is to ...
    • A Bazaar in Seendhiya's Camp 

      Broughton, T. D. (1813)
    • BDNF Val66Met polymorphism in patterns of neural activation in individuals with MDD and healthy controls 

      Lisiecka, Danuta M.; O'Hanlon, Erik; Fagan, Andrew J.; Carballedo, Angela; Morris, Derek; Suckling, John; Frodl, Thomas (Elsevier, 2015-06-13)
      Background: Rs6265 single nucleotide polymorphism, which influences brain-derived neurotrophic factor (BDNF) levels in the cortical and subcortical brain structures, may result in distinguished patterns of neural activation ...
    • Be Careful What You Wish For – Unexpected Policy Consequences 

      Kingsley, Danny A. (2015-06-24)
      The open access policy landscape in the UK is currently very convoluted and in some cases conflicted. For example, both the Research Councils of UK and Higher Education Funding Council of England have policies requiring ...
    • [Beach Road] Raffles School, Raffles Hotel. Drill Hall 

      Hill-Cottingham, F. T., 1878-1974 (Royal Commonwealth Society Library. Cambridge University Library. University of Cambridge., 2004-11-05)
    • The Beach, Zanzibar 

      A C Gomes and Son (Royal Commonwealth Society Library. Cambridge University Library. University of Cambridge., 2004-11-05)
    • Bear Encounter 

      Subashi, Siri Bhakta (2000)
    • Bear Encounter 

      Subashi, Siri Bhakta (2003)