Reminder: OWABI - Kate Lee - May 28, 10am UK time
Dear all, a kind reminder that the next OWABI seminar www.warwick.ac.uk/owabi<http://www.warwick.ac.uk/owabi> of the Season is on Thursday the 28th May at 10am UK time (a wrong date was circulated before, apologies for that!), when Kate Lee<https://profiles.auckland.ac.nz/kate-lee> <https://profiles.auckland.ac.nz/kate-lee> (University of Auckland) will talk about "Towards Robust and Scalable Bayesian Learning". The talk will be streamed on the OWABI MS Teams Channel General | OWABI Seminar: One World Approximate Bayesian Inference Seminar<https://teams.microsoft.com/l/team/19%3AdhZ_4e_XLNJzCXPAMzTvT6BZ5KShEETkd_wtTY52VI81%40thread.tacv2/conversations?groupId=9c061d11-f88c-4cee-938f-bf40e7393879&tenantId=09bacfbd-47ef-4465-9265-3546f2eaf6bc> at this link https://teams.microsoft.com/meet/382746871856192?p=U7SJQ144q6hLNVFGdS Meeting ID: 382 746 871 856 192 Passcode: FZ2gn73K Speaker: Kate Lee<https://profiles.auckland.ac.nz/kate-lee> (University of Auckland) Title: Towards Robust and Scalable Bayesian Learning Abstract: My talk consists of two parts. The first focuses on Generalised Bayesian Inference (GBI), where the loss hyperparameters are critical under model misspecification yet difficult to determine in a principled way. We introduce a Bayesian framework for hyperparameter inference using held-out data, enabling coherent estimation and uncertainty quantification, together with amortized generalized-posterior approximations that avoid repeated costly sampling across datasets and hyperparameter values. The second addresses scalability in simulation-based inference through data reduction, developing methods that learn informative low-dimensional summaries to enable efficient inference in complex settings, with applications to gravitational wave analysis. Keywords: GBI, SBI, amortized learning We're looking forward to seeing you next week, best, Massimiliano on the behalf of the OWABI Seminar Organisers ------ Dr. Massimiliano Tamborrino SFHEA Reader (Associate Professor) Department of Statistics WIHEA Fellow and Internationalisation Learning Circle Co-Lead University of Warwick https://warwick.ac.uk/tamborrino
participants (1)
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Massimiliano Tamborrino