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SUMMARY:Akash Sharma (Chalmers University of Technology & University of Go
 thenburg)
DTSTART:20240320T121500Z
DTEND:20240320T130000Z
DTSTAMP:20260422T155153Z
UID:gbgstats/47
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/gbgstats/47/
 ">Sampling on manifolds via Langevin diffusion</a>\nby Akash Sharma (Chalm
 ers University of Technology & University of Gothenburg) as part of Gothen
 burg statistics seminar\n\nLecture held in MVL14.\n\nAbstract\nWe derive e
 rror bounds for sampling and estimation using a discretization of an intri
 nsically defined Langevin diffusion on a compact Riemannian manifold. Two 
 estimators of linear functionals of invariant measure based on the discret
 ized Markov process are considered: a time-averaging estimator and an ense
 mble-averaging estimator. Imposing no restrictions beyond a nominal level 
 of smoothness on potential function\, first-order error bounds\, in discre
 tization step size\, on the bias and variances of both estimators are deri
 ved. We will also discuss conditions for extending analysis to the case of
  non-compact manifolds and different variants of the algorithm. We will pr
 esent numerical illustrations with distributions on the manifolds of posit
 ive and negative curvature which verify the derived bounds.\n\nJoint work 
 with Karthik Bharath (University of Nottingham)\, Alexander Lewis (Univers
 ity of Gottingen) and Michael Tretyakov (University of Nottingham)\n
LOCATION:https://researchseminars.org/talk/gbgstats/47/
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