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SUMMARY:Elizabeth Baker (DTU)
DTSTART:20250611T111500Z
DTEND:20250611T120000Z
DTSTAMP:20260422T155154Z
UID:gbgstats/83
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/gbgstats/83/
 ">Conditioning diffusion processes with score matching methods</a>\nby Eli
 zabeth Baker (DTU) as part of Gothenburg statistics seminar\n\nLecture hel
 d in MVL14.\n\nAbstract\nIn stochastic optimal control and conditional gen
 erative modelling\, a central computational task is to modify a reference 
 diffusion process to maximise a given terminal-time reward. Most existing 
 methods require this reward to be differentiable\, using gradients to stee
 r the diffusion towards favourable outcomes. However\, in many practical s
 ettings\, like diffusion bridges\, the reward is singular\, taking an infi
 nite value if the target is hit and zero otherwise. We introduce a novel f
 ramework\, based on Malliavin calculus and path-space integration by parts
 \, that enables the development of methods robust to such singularities. T
 his allows our approach to handle a broad range of applications\, includin
 g classification\, diffusion bridges\, and conditioning without the need f
 or artificial observational noise.\n
LOCATION:https://researchseminars.org/talk/gbgstats/83/
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