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April 2018

BSU Seminar: “Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities”

April 26 @ 2:30 pm - 3:30 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Speaker: Prof. François Caron, University of Oxford Title: "Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities" Abstract: In this talk I will describe a  novel  statistical  model  for  sparse  networks with  overlapping  community Structure and heavy tailed degree distributions. The model is based on representing the graph as an exchangeable point process, and naturally generalizes existing probabilistic models with overlapping block-structure to the sparse regime. Our construction builds on vectors of completely random measures, and has interpretable parameters, each node…

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May 2018

BSU Seminar: “Cox-process representation and inference for stochastic reaction-diffusion processes”

May 10 @ 2:30 pm - 3:30 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

By: Dr Guido Sanguinetti, University of Edinburgh Title: “Cox-process representation and inference for stochastic reaction-diffusion processes” Abstract: Complex behaviour in many systems arises from the stochastic interactions of spatially distributed particles or agents. Stochastic reaction-diffusion processes are widely used to model such behaviour in disciplines ranging from biology to the social sciences, yet they are notoriously difficult to simulate and calibrate to observational data. On the other hand, spatio-temporal point processes offer several computational advantages from the statistical perspective, and can be coupled…

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BSU Seminar: “Optimal bootstrapping with dependent data”

May 29 @ 2:30 pm - 3:30 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

By: Prof Alastair Young, Imperial College London Title:"Optimal bootstrapping with dependent data" Abstract: We consider nonparametric bootstrap techniques, used to estimate error quantities in problems of statistical inference. Given a data sample of n data points, bootstrap quantities are generally constructed by generation, through resampling, of a large number of `bootstrap samples', each consisting also of n data points. Exceptions are techniques such as subsampling and the m out of n bootstrap, which may be required to ensure consistency of the…

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June 2018

BSU Seminar: “Mass spectrometry-based proteomics: challenges and opportunities”

June 7 @ 2:30 pm - 3:30 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

By: Dr Laurent Gatto, University of Cambridge Title:"Mass spectrometry-based proteomics: challenges and opportunities" Abstract: Mass spectrometry is the technique of choice to study proteins in a high throughput fashion. And while the final outputs that you might be presented looks like a typical omics table, with assayed proteins along the row and samples along the columns, the characteristics of mass spectrometry result in some interesting features. In my talk, I will describe how mass spectrometry is used to identify and quantify…

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