MS016C Scientific Machine Learning for Nonlinear Model Reduction III
Main Organizer:
Prof.
Boris Kramer
(
University of California San Diego
, United States
)
Chaired by:
Prof. Boris Kramer (University of California San Diego , United States) , Prof. Benjamin Peherstorfer (Courant Institute of Mathematical Sciences, New York University , United States)
Prof. Boris Kramer (University of California San Diego , United States) , Prof. Benjamin Peherstorfer (Courant Institute of Mathematical Sciences, New York University , United States)
Scheduled presentations:
-
Fast, Data-Assisted Simulations of Recurrent Flows using a Deviation-Propagation Approach
-
Efficient subspace-distance-enhanced nonlinear model order reduction for parametric CFD
-
Deep Convolutional–Transformer Models for Stable Autoregressive Evolution of Parametric Partial Differential Equations
-
Nonlinear Model Order Reduction of Multiscale Problems using Graph-Based Manifold Learning Methods and Hyperreduction Techniques
-
RRAE-Based Nonlinear Compressed Sensing for Field Reconstruction and PDE Hyper-Reduced Resolution
-
Effective Drone Formation Operations Dedicated to Safe Ground Vehicle Motions in the Presence of Obstacles
