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  • 3D object reconstruction using multiple views 

    Kim, Donghoon (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2011)
    3D object modelling from multiple view images has recently been of increasing interest in computer vision. Two techniques, Visual Hull and Photo Hull, have been extensively studied in the hope of developing 3D shape ...
  • A diagnostic for the general linear model : an application to Time Series 

    Sullivan, Carl (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2002)
    An outlier is an observation which is thought to be unusual. The detection of such extreme values is an important issue. Developing a model based on data containing even a single outlier can seriously bias population ...
  • A new method to implement Bayesian inference on stochastic differential equation models 

    Joshi, Chaitanya (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2011)
    Stochastic differential equations (SDEs) are widely used to model numerous real-life phenomena. However, transition densities of most of the SDE models used in practice are not known, making both likelihood based and ...
  • A risk assessment tool for highly energetic break-up events during the atmospheric re-entry 

    De Persis, Cristina (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2017)
    Most unmanned space missions end up with a destructive atmospheric re-entry. From ten to forty percent of a re-entering satellite’s mass may survive re-entry and hit the Earth’s surface. This has the potential to be a ...
  • Advances in Bayesian model development and inversion in multivariate inverse inference problems : with application to palaeoclimate reconstruction 

    Sweeney, James (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2012)
    An extremely challenging example of a multivariate inverse inference problem is the statistical reconstruction of palaeoclimate from fossil pollen data, which represents the motivating research problem considered in this ...
  • An exploratory study of gender segregation in investment management in Ireland 

    Sheerin, Corina (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2013)
    Despite the entry of women in recent years, Investment Management remains a male domain. The absence of women is most notable in the fund management suite and on the trading floor (the most lucrative sub sectors of the ...
  • Bayesian approaches to content-based image retrieval 

    Stefanou, Georgios Andrea (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006)
    This thesis addresses some issues in the relatively new field of Content-Based Image Retrieval. Content-based image retrieval is a technique that uses the visual content of images to aid searches from large scale image ...
  • Bayesian inference for misaligned irregular time series with application to palaeoclimate reconstruction 

    Doan, Thinh K. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2015)
    This thesis proposes new Bayesian methods to jointly analyse misaligned irregular time series. Temporal misalignment occurs wdien multiple irregularly spaced time series are considered together, or when the time periods ...
  • Bayesian inference for short term traffic forecasting 

    Mai, Tiep K. (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2013)
    In intelligent transport systems, short term traffic forecasting is one of the most important problems, reflecting the network state in the near future and feeding information to other application modules. Even though ...
  • Bayesian kernel classification for high dimensional data with variable selection 

    Domijan, Katarina (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2009)
    High dimensional data sets, where the dimension of the measurements exceeds the number of samples, arise in many application domains. In particular, the development of genomic and proteomic technologies in the last decade ...
  • Bayesian modelling of short fatigue crack growth and coalescence 

    Walsh, Cathal Dominic (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2000)
    Failure of metal structures is caused by cracks appearing and growing in the material until the strength of the structure is compromised. The way in which such cracks grow in metal has been researched extensively; the great ...
  • Competing risks of default and prepayment of mortgage market 

    OLAJUBU, OLUWATOBILOBA JOHN JOHN (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)
    Using a large data set on the Single family home loans from The Federal Home Loan Mortgage Corporation (FHLMC), sponsored by the US government, this research studies the economic factors affecting the competing risks of ...
  • Deletion diagnostics for the linear mixed model 

    Dillane, Dominic Mark (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2006)
    Modeling data is an integral element of modern statistical analysis. Methodological developments combined with the explosion in computing power over the past ten to fifteen years have greatly enhanced statisticians' ability ...
  • Efficient and scalable inference for generalized student - T process models 

    ROETZER, GERNOT RUDOLF (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)
    Gaussian Processes are a popular, nonparametric modelling framework for solving a wide range of regression problems. However, they are suffering from 2 major shortcomings. On the one hand, they require efficient, approximate ...
  • Fast approximate inverse Bayesian inference in non-parametric multivariate regression with application to palaeoclimate reconstruction 

    Salter-Townshend, Michael (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2009)
    Bayesian statistical methods often involve computationally intensive inference procedures. Sampling algorithms represent the current standard for fitting and testing models. Such methods, while flexible, are computationally ...
  • Fast sequential parameter inference for dynamic state space models 

    Bhattacharya, Arnab (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2012)
    Many problems in science require estimation and inference on systems that generate data over time. Such systems, quite common in statistical signal processing, time series analysis and econometrics, can be stated in a ...
  • Female entrepreneurship : an exploratory study of women entrepreneurs in Ireland 

    Humbert, Anne Laure (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2007)
    This thesis consists of an exploratory study of female entrepreneurship in Ireland, focusing on the motivations, obstacles and work/life balance experiences of entrepreneurs. The research relies on a combination of ...
  • Image Restoration Using Deep Learning 

    ALBLUWI, FATMA HAMED (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2020)
    In this thesis, we propose several convolutional neural network (CNN) architectures with fewer parameters compared to state-of-the-art deep structures to restore original images from degraded versions. Employing fewer ...
  • The Impact of Performing a Network Meta-Analysis with Imperfect Evidence 

    LEAHY, JOY (Trinity College Dublin. School of Computer Science & Statistics. Discipline of Statistics, 2019)
    Network meta-analysis (NMA) is an important aspect of evidence synthesis in a clinical setting, as it allows us to compare treatments which may not have been analysed in the same trial. In an ideal scenario we would have ...
  • Importance resampling MCMC : a methodology for cross-validation in inverse problems and its applications in model assessment 

    Bhattacharya, Sourabh (Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005)
    This thesis presents a methodology for implementing cross-validation in the context of Bayesian modelling of situations we loosely refer to as 'inverse problems'. It is motivated by an example from palaeoclimatology in ...