BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Max Welling (University of Amsterdam) DTSTART:20200721T163000Z DTEND:20200721T174500Z DTSTAMP:20260423T021059Z UID:IASML/11 DESCRIPTION:Title: G raph Nets: The Next Generation\nby Max Welling (University of Amsterda m) as part of IAS Seminar Series on Theoretical Machine Learning\n\n\nAbst ract\nIn this talk I will introduce our next generation of graph neural ne tworks. GNNs have the property that they are invariant to permutations of the nodes in the graph and to rotations of the graph as a whole. We claim this is unnecessarily restrictive and in this talk we will explore extensi ons of these GNNs to more flexible equivariant constructions. In particula r\, Natural Graph Networks for general graphs are globally equivariant und er permutations of the nodes but can still be executed through local messa ge passing protocols. Our mesh-CNNs on manifolds are equivariant under SO( 2) gauge transformations and as such\, unlike regular GNNs\, entertain non -isotropic kernels. And finally our SE(3)-transformers are local message p assing GNNs\, invariant to permutations but equivariant to global SE(3) tr ansformations. These developments clearly emphasize the importance of geom etry and symmetries as design principles for graph (or other) neural netwo rks.\n\nJoint with: Pim de Haan and Taco Cohen (Natural Graph Networks) Pi m de Haan\, Maurice Weiler and Taco Cohen (Mesh-CNNs) Fabian Fuchs and Dan iel Worrall (SE(3)-Transformers)\n LOCATION:https://researchseminars.org/talk/IASML/11/ END:VEVENT END:VCALENDAR