Session | ||
MS4: Kernel Methods in Data Analysis and Computational Science
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Presentations | ||
2:00pm - 2:30pm
Gaussian Process Surrogate for Bayesian Parameter Estimation Involving Incompressible Fluids 1University of Bayreuth; 2University of New South Wales, Australia 2:30pm - 3:00pm
How many neurons do we need? A refined analysis for shallow networks trained with gradient descent TU Braunschweig 3:00pm - 3:30pm
Some results on the NTK spectrum and spectral bias of neural networks in the kernel regime 1University of California, Los Angeles, USA; 2Max Planck Institute for Mathematics in the Sciences, Leipzig 3:30pm - 4:00pm
Kernel Methods for Koopman-based Modeling Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg |