UDRC Themed Meeting on Scalable Signal Processing with Bayesian Graphical Models

Plenary talk: Convergence Rates for a Class of Monte Carlo Estimators Based on Stein's Method, Mark Girolami, Imperial College London - Abstract
Sensor Fusion, David Cormack, Heriot-Watt University; James Hopgood, University of Edinburgh
Advanced MCMC, Kostas Zygalakis, Heriot-Watt University

Approximate Message Passing and Expectation Propagation, Yoann Altmann, Heriot-Watt University
Scalable Opportunistic Calibration of Fusion Networks, Murat Uney, CMRE
Scaling signal processing for industry needs, David Greig, Leonardo
Dstl challenges, Jordi Barr, Dstl; Gary Heald, Dstl

Event Date:  Wednesday, February 20, 2019 - 09:00
Location:  Edinburgh
As part of the UDRC phase III, a first themed meeting on Scalable Signal Processing with Bayesian Graphical Models will be held in Edinburgh on Wednesday, 20th February. This event is intended for academic researchers, industrial partners and Dstl staff to learn about and discuss current trends in scalable Bayesian methods.
The program will consists of a series of talks covering Bayesian sensor fusion, Bayesian networks, approximate message passing and advanced Monte Carlo sampling techniques, followed by a networking session. We will also present a Dstl Challenge competition.
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