BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Geometric Gaussian Processes - Dr Viacheslav Borovitskiy - School 
 of Informatics Institute for Adaptive and Neural Computation\, University 
 of Edinburgh 
DTSTART:20260218T150500Z
DTEND:20260218T155500Z
UID:TALK237238@talks.cam.ac.uk
CONTACT:Ben Karniely
DESCRIPTION:Gaussian processes (GPs) are often considered to be the gold s
 tandard in settings where well-calibrated predictive uncertainty is of key
  importance\, such as decision making.\n\nIt is important for applications
  to have a class of  “general purpose” GPs. Traditionally\, these are 
 the stationary processes\, e.g. RBF or Matérn GPs\, at least for the usua
 l vectorial inputs. For non-vectorial inputs\, however\, there is often no
  such class. This state of affairs hinders the use of GPs in a number of a
 pplication areas ranging from robotics to drug design.\n\nIn this talk\, I
  will consider GPs taking inputs on a manifold\, on a node set of a graph\
 , or in a discrete “space” of graphs. I will discuss a framework for d
 efining the appropriate general purpose GPs\, as well as the analytic and 
 numerical techniques that make them tractable.\n\n\nLink to join virtually
 : https://cam-ac-uk.zoom.us/j/89473073451\n\nA recording of this talk is a
 vailable at the following link: https://www.cl.cam.ac.uk/seminars/wednesda
 y/video/\n\nThis talk is being recorded. If you do not wish to be seen in 
 the recording\, please avoid sitting in the front six rows of the central 
 section in the lecture theatre. Any questions asked will also be included 
 in the recording. The recording will be made available on the Department
 ’s webpage
LOCATION:Lecture Theatre 1\, Computer Laboratory\, William Gates Building
END:VEVENT
END:VCALENDAR