176 citations · 266 across the 19 of their papers we have counts for
19 papers
Data-driven local operator finding for reduced-order modelling of plasma systems: II. Application to parametric dynamics
Farbod Faraji, Maryam Reza, Aaron Knoll +1
Real-world systems often exhibit dynamics influenced by various parameters, either inherent or externally controllable, necessitating models capable of reliably capturing these par…
Data-driven local operator finding for reduced-order modelling of plasma systems: I. Concept and verifications
Farbod Faraji, Maryam Reza, Aaron Knoll +1
Reduced-order plasma models that can efficiently predict plasma behavior across various settings and configurations are highly sought after yet elusive. The demand for such models…
Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks
Jonas Kneifl, Jörg Fehr, Steven L. Brunton +1
Crash simulations play an essential role in improving vehicle safety, design optimization, and injury risk estimation. Unfortunately, numerical solutions of such problems using sta…
Ensemble Principal Component Analysis
Olga Dorabiala, Aleksandr Aravkin, J. Nathan Kutz
Efficient representations of data are essential for processing, exploration, and human understanding, and Principal Component Analysis (PCA) is one of the most common dimensionalit…
HyperSINDy: Deep Generative Modeling of Nonlinear Stochastic Governing Equations
Mozes Jacobs, Bingni W. Brunton, Steven L. Brunton +2
The discovery of governing differential equations from data is an open frontier in machine learning. The sparse identification of nonlinear dynamics (SINDy) \citep{brunton_discover…
Multi-fidelity reduced-order surrogate modeling
Paolo Conti, Mengwu Guo, Andrea Manzoni +3
High-fidelity numerical simulations of partial differential equations (PDEs) given a restricted computational budget can significantly limit the number of parameter configurations…