Matt Moores

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PDRA on the EPSRC funded project "In Situ Nanoparticle Assemblies for Healthcare Diagnostics and Therapy" with Prof. Mark Girolami, in collaboration with the University of Strathclyde, Glasgow. My dissertation involved the development of Bayesian computational methods for spatial analysis of images, with applications to medical imaging and satellite remote sensing. I was previously involved in the Visible Cell project at the Institute for Molecular Bioscience, UQ. I also have over a decade of experience in R&D, having worked for various international companies.

bayesian markov ranodm field image analysis abc mcmc intractable likelihood r computational statistics rcpp satellite rstats armadillo bayesian modelling sequential monte carlo smc ct tga thermogravimetric analysis inverse problems medical imaging ggplot clustering pca modis rastervis rgdal usgs nlcd landsat nasa eigen openmp functional data analysis raman spectroscopy statistics computer programming

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Aktuellste Beliebteste SlideShares

Matt Moores

Bayesian Inference and Uncertainty Quantification for Inverse Problems

bayesImageS: an R package for Bayesian image analysis

Exploratory Analysis of Multivariate Data

R package bayesImageS: Scalable Inference for Intractable Likelihoods

bayesImageS: Bayesian computation for medical Image Segmentation using a hidden Potts Model

Approximate Bayesian computation for the Ising/Potts model

Importing satellite imagery into R from NASA and the U.S. Geological Survey

Accelerating Pseudo-Marginal MCMC using Gaussian Processes

R package 'bayesImageS': a case study in Bayesian computation using Rcpp and OpenMP

Bayesian modelling and computation for Raman spectroscopy

Final PhD Seminar

Precomputation for SMC-ABC with undirected graphical models

Intro to ABC

Pre-computation for ABC in image analysis

Variational Bayes

Parallel R

Informative Priors for Segmentation of Medical Images