REDUCED ORDER MODELS APPROXIMATION THEORY MACHINE LEARNING SURROGATES, EMULATORS AND SIMULATORS CONFERENCE 2020

Abstract

This workshop is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via Reduced-order models; Approximation theory; Machine learning; Surrogates, Emulators, and Simulators (RAMSES) in the setting of parametrized partial differential equations (PDEs) with sparse and noisy data in high-dimensional parameter spaces. Topics of the workshop represent promising approaches for improvements in the way model approximation in the PDEs setting is carried out.

Document Details

Document Type
DoD Grant Award
Publication Date
Aug 11, 2021
Source ID
FA86552017023

Entities

People

  • Max Gunzburger

Organizations

  • Air Force Office of Scientific Research
  • Florida State University
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Calculus or Mathematical Analysis
  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Space