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The Battle for Spaces and Places in Russia's Civil War
(Wiley, 2016)After the October Revolution, the Bolsheviks needed to battle to control Russia’s urban and rural spaces to win the war, exert state power and transform mentalities. This article argues that revolutionary tribunals played ... 
Battle of background leakage assessment for Water Networks (BBLAWN) at WDSA conference 2014
(Elsevier, 2014)The Battle of Background Leakage Assessment for Water Networks (BBLAWN) is the fifth in a series of "Battle Competitions" dating back to the Battle of the Water Networks (BWN) in 1985 and, more recently, the Battle of the ... 
The Battle of the Water Networks II (BWNII)
(American Society of Civil Engineers, 20130518)The Battle of the Water Networks II (BWNII) is the latest of a series of competitions related to the design and operation of water distribution systems (WDSs) undertaken within the Water Distribution Systems Analysis ... 
Battle of Waterloo Peepshow
(20090624) 
Battleship Potemkin
(20091110) 
Baudrillard's nihilism and the end of theory
(Telos Press, 1998) 
The Bayesian Decision Tree Technique with a Sweeping Strategy
(2004)The uncertainty of classification outcomes is of crucial importance for many safety critical applications including, for example, medical diagnostics. In such applications the uncertainty of classification can be reliably ... 
Bayesian detection of planetary transits. A modified version of the GregoryLoredo method for Bayesian periodic signal detection
(EDP Sciences, 2002)The detection of planetary transits in stellar photometric lightcurves is poised to become the main method for finding substantial numbers of terrestrial planets. The FrenchEuropean mission COROT (foreseen for launch in ... 
Bayesian estimation and classification with incomplete data using mixture models
(IEEE, 2004)Reasoning from data in practical problems is frequently hampered by missing observations. Mixture models provide a powerful general semiparametric method for modelling densities and have close links to radial basis function ... 
A Bayesian expected error reduction approach to Active Learning
(University of ExeterEngineering, Mathematics and Physical Sciences, 20110428)There has been growing recent interest in the field of active learning for binary classification. This thesis develops a Bayesian approach to active learning which aims to minimise the objective function on which the learner ... 
A Bayesian Framework for Active Learning
(Institute of Electrical and Electronics Engineers (IEEE), 2010)We describe a Bayesian framework for active learning for nonseparable data, which incorporates a query density to explicitly model how new data is to be sampled. The model makes no assumption of independence between queried ... 
A Bayesian framework for verification and recalibration of ensemble forecasts: How uncertain is NAO predictability?
(arXiv.org, 20150408)Predictability estimates of ensemble prediction systems are uncertain due to limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that ... 
Bayesian history matching of complex infectious disease models using emulation: a tutorial and a case study on HIV in Uganda
(Public Library of Science, 201501)Advances in scientific computing have allowed the development of complex models that are being routinely applied to problems in disease epidemiology, public health and decision making. The utility of these models depends ... 
Bayesian inductively learned modules for safety critical systems
(Interface Foundation of North America, Inc., 2003)This work examines the use of Bayesian inductively learned software modules for safety critical systems. Central to the safety critical application is the desire to generate confidence measures associated with predictions. ... 
A Bayesian methodology for estimating uncertainty of decisions in safetycritical systems
(IOS Press, 2006)Uncertainty of decisions in safetycritical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) ... 
Bayesian model choice in cumulative link ordinal regression models
(International Society for Bayesian Analysis (ISBA), 20150128)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 nonproportional odds ... 
Bayesian modelling of recurrent pipe failures in urban water systems using nonhomogeneous Poisson processes with latent structure
(University of ExeterCollege of Engineering, Mathematics and Physical Sciences, 20100712)Recurrent events are very common in a wide range of scientific disciplines. The majority of statistical models developed to characterise recurrent events are derived from either reliability theory or survival analysis. ... 
Bayesian Spectral Analysis with Studentt Noise
(Institute of Electrical and Electronics Engineers (IEEE), 20140601)We introduce a Bayesian spectral analysis model for onedimensional signals where the observation noise is assumed to be Studentt distributed, for robustness to outliers, and we estimate the posterior distributions of the ... 
Bayesian unsupervised learning with multiple data types
(Walter de Gruyter, 2009)We propose Bayesian generative models for unsupervised learning with two types of data and an assumed dependency of one type of data on the other. We consider two algorithmic ap proaches, based on a correspondence model ...