Department of Electrical and Systems Engineering, University of Pennsylvania; Department of Mechanical Engineering and Applied Mechanics, University of Pennsylvania; Graduate Program in Applied Mathematics and Computational Science, University of Pennsylvania
Jacob Seidman
Operator Learning;Manifold Learning;Functional Data;PDEs;Nonlinear Dimension Reduction
NOMAD: Nonlinear Manifold Decoders for Operator Learning