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SUMMARY:Unconventional Discretizations for Geometry Processing - Justin So
 lomon (Massachusetts Institute of Technology)
DTSTART:20260416T091500Z
DTEND:20260416T101500Z
UID:TALK244018@talks.cam.ac.uk
DESCRIPTION:With applications to computer graphics and engineering\, the f
 ield of geometry processing seeks to develop a computatoinal toolkit for d
 esigning\, manipulating\, and understanding 3D geometry.&nbsp\; Classical 
 algorithms for geometry processing are built on the foundations of the fin
 ite element method (FEM) and other techniques for discretizing and solving
  variational problems in geometry.&nbsp\; In this talk\, I will explore al
 ternative discretizations for geometry processing problems that build on m
 odern machinery of automatic differentiation\, stochastic gradient descent
 \, and nonlinear function spaces.&nbsp\; Largely inspired by practical rob
 ustness and efficiency demands of practitioners in geometry processing\, o
 ur work also suggests new directions for applied and theoretical research 
 in PDE\, spectral geometry\, and related fields.\nJoint work with Albert C
 hern\, Ana Dodik\, Mina Konaković Luković\, Ahmed Mahmoud\, David Palmer
 \, Dmitriy Smirnov\, Vincent Sitzmann\, Oded Stein\, Anh Truong\, Stephani
 e Wang\, and other members of the MIT Geometric Data Processing Group.
LOCATION:Seminar Room 1\, Newton Institute
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