Reply To: Conference on inference methods for mathematical biology

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#7634
ben18785
Participant

Dear all,

We would like to invite online attendees to the above conference taking place on the 23rd / 24th May 2022. Online tickets cost £20 for two days and can be purchased here: https://fixr.co/event/inference-for-expensive-systems-in-mathematical-bi-tickets-517620015

The talks include the following, which will be livestreamed from Oxford. Online participants will be able to ask the presenters questions through a messenger service.

– Measuring the accuracy of likelihood-free inference, Aden Forrow, University of Oxford
– Non-stationary noise analysis of whole-cell currents from hERG expression systems, Alejandra D Herrera Reyes, University of Nottingham
– Estimating transmission and prevalence from sequence, occurrence, (and possibly serological) data, Alexander Zarebski, University of Oxford
– Some results on MCMC algorithms for intractable likelihoods, George Deligiannidis, University of Oxford
– Statistical calibration of pattern formation models, Heikki Haario, Lappeenranta University of Technology
– Nonreversible MCMC for latent phylogenetic trees, Jere Koskela, University of Warwick
– Quantifying the relative information in noisy epidemic time series, Kris Parag, University of Bristol
– Kernel Stein discrepancy minimization for MCMC thinning in cardiac electrophysiology, Marina Riabiz, King’s College London
– Four ways to fit an ion channel model, Michael Clerx, University of Nottingham
– History Matching – an alternative way of inference for biological systems, Peter Challenor, University of Exeter
– Monte Carlo methods based on repulsive point processes for generic expensive models, Rémi Bardenet, Ecole Centrale de Lille
– Improved Bayesian inference for ODEs using adjoint methods for gradient-based sampling and adaptive step size selection, Richard Creswell, University of Oxford
– Efficient Bayesian inference for mechanistic modelling with high-throughput data, Ruth Baker, University of Oxford
– Practical parameter identifiability applied to a model of autoimmune myocarditis, Solveig van der Vegt, University of Oxford
– Parameter inference with topological approximate bayesian computation, Tom Thorne, University of Surrey

Note that the conference will also be taking place in person, and the above tickets do not allow in-person attendance. Best, Conference organising committee

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