Physics-Informed Sampling Procedure For Reduced Order Models

[libROM tutorial] Physics-informed sampling procedure for reduced order models

DDPS | Non-intrusive reduced order models using physics informed neural networks

Livermore Lab Events

DDPS | Deep learning for reduced order modeling

Livermore Lab Events

[libROM tutorial] Local reduced order models and interpolation-based parameterization | #ROM

[WCCM2022] Nonlinear manifold to component-wise reduced order models towards multi-scale problems

Reduced Order Models (ROMs)? | Podcast Clips🎙️

Jousef Murad | Deep Dive

Accelerating design optimization with reduced order models | #design #optimization #ROM #MOR

Reduced Order Modeling Using Machine Learning

Liliana Borcea - Waveform inversion via reduced order modeling

Physics Informed Machine Learning

[libROM tutorial] Projection-based reduced order model for Poisson equation | #poisson #ROM #MOR

CT11 - Reduced Order Modeling

Physics-Informed Dynamic Mode Decomposition (PI-DMD)

[libROM tutorial] Projection-based reduced order model for nonlinear system | #ROM #nonlinear #data

MFEM Workshop 2022 | Reduced Order Modeling for FE Simulations with MFEM & libROM

Livermore Lab Events

DDPS | Efficient nonlinear manifold reduced order model

Livermore Lab Events

Scientific Machine Learning: Physics-Informed Neural Networks with Craig Gin

Cambridge University Press

Rudy Geelen - Learning physics-based reduced-order models from data using quadratic manifolds

The Alan Turing Institute

Andrea Manzoni (POLIMI) - Deep learning reduced order models for numerical approximation of PDEs

MaLGa - Machine Learning Genoa Center