CSE19 - MS71-1: Projection-based Model Reduction: Formulations for Physics-based Machine Learning Presentation: Karen E Willcox, University of Texas at Austin, U.S., 22 min 31 sec

CSE19 - MS71-1: Projection-based Model Reduction: Formulations for Physics-based Machine Learning Document: CSE19 - MS71-1: Projection-based Model Reduction: Formulations for Physics-based Machine Learning

CSE19 - MS71-2: Learning Parameters and Constitutive Relationships with Physics Informed Deep Neural Networks Presentation: Alexander Tartakovsky, Pacific Northwest National Laboratory, U.S., 15 min 16 sec

CSE19 - MS71-2: Learning Parameters and Constitutive Relationships with Physics Informed Deep Neural Networks Document: CSE19 - MS71-2: Learning Parameters and Constitutive Relationships with Physics Informed Deep Neural Networks

CSE19 - MS71-4: Machine-learning Error Models for Approximate Solutions to Parameterized Systems of Nonlinear Equations Presentation: Brian A Freno, Sandia National Laboratories, U.S., 18 min 53 sec

CSE19 - MS71-4: Machine-learning Error Models for Approximate Solutions to Parameterized Systems of Nonlinear Equations Document: CSE19 - MS71-4: Machine-learning Error Models for Approximate Solutions to Parameterized Systems of Nonlinear Equations