Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via
Spectral Submanifolds

Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds

13 January 2022

Mattia Cenedese

Bastian Bäuerlein

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Papers citing "Data-Driven Modeling and Prediction of Non-Linearizable Dynamics via Spectral Submanifolds"

19 / 19 papers shown

Title
A discrete physics-informed training for projection-based reduced order models with neural networks N. Sibuet S. A. D. Parga J. R. Bravo R. Rossi 61 0 0 31 Mar 2025
Hybrid Time-Domain Behavior Model Based on Neural Differential Equations and RNNs Zenghui Chang Yang Zhang Hu Tan Hong Cai Chen 60 0 0 28 Mar 2025
Data-Driven Soft Robot Control via Adiabatic Spectral Submanifolds Roshan S. Kaundinya J. I. Alora Jonas G. Matt Luis A. Pabon Marco Pavone George Haller 83 0 0 13 Mar 2025
On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions Jake Buzhardt C. Ricardo Constante-Amores Michael D. Graham 171 2 0 20 Nov 2024
Distributed computing for physics-based data-driven reduced modeling at scale: Application to a rotating detonation rocket engine Ionut-Gabriel Farcas Rayomand P. Gundevia R. Munipalli Karen E. Willcox AI4CE 120 1 0 13 Jul 2024
Machine-learning invariant foliations in forced systems for reduced order modelling R. Szalai 59 1 0 21 Mar 2024
Information theory for data-driven model reduction in physics and biology Matthew S. Schmitt Maciej Koch-Janusz Michel Fruchart Daniel S. Seara Michael Rust Vincenzo Vitelli 85 5 0 11 Dec 2023
Generative learning for nonlinear dynamics William Gilpin AI4CE PINN 123 27 0 07 Nov 2023
Mori-Zwanzig latent space Koopman closure for nonlinear autoencoder Priyam Gupta Peter J. Schmid D. Sipp T. Sayadi Georgios Rigas 118 5 0 16 Oct 2023
Robust Nonlinear Reduced-Order Model Predictive Control J. I. Alora Luis A. Pabon Johannes Köhler Mattia Cenedese Edward Schmerling Melanie Zeilinger George Haller Marco Pavone 40 3 0 11 Sep 2023
Learning Nonlinear Projections for Reduced-Order Modeling of Dynamical Systems using Constrained Autoencoders Samuel E. Otto G. Macchio C. Rowley AI4CE 59 22 0 28 Jul 2023
Discovering Causal Relations and Equations from Data Gustau Camps-Valls Andreas Gerhardus Urmi Ninad Gherardo Varando Georg Martius E. Balaguer-Ballester Ricardo Vinuesa Emiliano Díaz L. Zanna Jakob Runge PINN AI4Cl AI4CE CML 108 77 0 21 May 2023
Latent Dynamics Networks (LDNets): learning the intrinsic dynamics of spatio-temporal processes Francesco Regazzoni S. Pagani M. Salvador Luca Dede' A. Quarteroni AI4CE 55 7 0 28 Apr 2023
Benchmarking sparse system identification with low-dimensional chaos A. Kaptanoglu Lanyue Zhang Zachary G. Nicolaou Urban Fasel Steven L. Brunton 103 24 0 04 Feb 2023
Changes from Classical Statistics to Modern Statistics and Data Science Kai Zhang Shan-Yu Liu M. Xiong 92 0 0 30 Oct 2022
Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots J. I. Alora Mattia Cenedese Edward Schmerling George Haller Marco Pavone 173 31 0 13 Sep 2022
Data-driven reduced order models using invariant foliations, manifolds and autoencoders R. Szalai AI4CE 55 10 0 24 Jun 2022
Enhancing Computational Fluid Dynamics with Machine Learning Ricardo Vinuesa Steven L. Brunton AI4CE 188 385 0 05 Oct 2021
Data-driven Nonlinear Model Reduction to Spectral Submanifolds in Mechanical Systems Mattia Cenedese Joar Axås Haocheng Yang M. Eriten George Haller 154 41 0 05 Oct 2021