BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Marcelo Pereyra (Heriot-Watt University) DTSTART:20200611T163000Z DTEND:20200611T173000Z DTSTAMP:20260423T003259Z UID:MPML/3 DESCRIPTION:Title: Eff icient Bayesian computation by proximal Markov chain Monte Carlo: when Lan gevin meets Moreau\nby Marcelo Pereyra (Heriot-Watt University) as par t of Mathematics\, Physics and Machine Learning (IST\, Lisbon)\n\n\nAbstra ct\nThis talk summarises some new developments in Bayesian statistical met hodology for performing inference in high-dimensional inverse problems wit h an underlying convex geometry. We pay particular attention to problems r elated to imaging sciences and to new stochastic computation methods that tightly combine proximal convex optimisation and Markov chain Monte Carlo sampling techniques. The new computation methods are illustrated with a ra nge of imaging experiments\, where they are used to perform uncertainty qu antification analyses\, automatically adjust regularisation parameters\, a nd objectively compare alternative models in the absence of ground truth.\ n LOCATION:https://researchseminars.org/talk/MPML/3/ END:VEVENT END:VCALENDAR