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UID:20260910T123524EDT-2646DvMMvj@132.216.98.100
DTSTAMP:20260910T163524Z
DESCRIPTION:Title:Deep neural networks for solving differential equations o
 n general orientable surfaces.\n\nAbstract:We present a general method for
  solving partial differential equations on orientable surfaces using deep 
 neural networks. The method rests on embedding the given differential equa
 tion on a surface in a higher-dimensional Cartesian space and solving the 
 differential equations in extrinsic coordinates that are then restricted i
 n a suitable way to the surface itself. The solution is approximated with 
 a neural network\, hence allowing for derivatives being computed using aut
 omatic differentiation. We illustrate the method by solving the shallow-wa
 ter equations on the sphere\, and various reaction-diffusion equations on 
 general surfaces such as the bumpy sphere\, Boy's surface and the Stanford
  bunny. This is joint work with Roman O. Popovych.\n\n \n\nApplied Mathema
 tics seminar\n	To register contact : appliedseminars [at] math.mcgill.ca\n
 \nJoin Zoom Meeting https://us06web.zoom.us/j/85327310903?pwd=SlhEak53S2xr
 NkVYKzl4YUd5KzBudz09\n\nMeeting ID: 853 2731 0903\n\nPasscode: 383854\n
DTSTART:20220110T210000Z
DTEND:20220110T220000Z
SUMMARY:Alex Bihlo (Memorial University)
URL:https://www.mcgill.ca/mathstat/channels/event/alex-bihlo-memorial-unive
 rsity-336083
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