Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling

11 September 2021

Papers citing "Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling"

19 / 19 papers shown

Title
Discovering Symbolic Differential Equations with Symmetry Invariants Jianke Yang Manu Bhat Bryan Hu Yadi Cao Nima Dehmamy Robin Walters Rose Yu 4 0 0 17 May 2025
Equilibrium Conserving Neural Operators for Super-Resolution Learning Vivek Oommen Andreas E. Robertson Daniel Diaz Coleman Alleman Zhen Zhang Anthony D. Rollett George Karniadakis Rémi Dingreville 35 1 0 18 Apr 2025
Generalizing the SINDy approach with nested neural networks Camilla Fiorini Clément Flint Louis Fostier Emmanuel Franck Reyhaneh Hashemi Victor Michel-Dansac Wassim Tenachi 76 1 0 28 Jan 2025
Efficiently Parameterized Neural Metriplectic Systems Anthony Gruber Kookjin Lee Haksoo Lim Noseong Park Nathaniel Trask 68 1 0 28 Jan 2025
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia Jan van Gemert Daan Brinks Nergis Tömen 38 0 0 02 Oct 2024
Symmetry-Informed Governing Equation Discovery Jianke Yang Wang Rao Nima Dehmamy Robin Walters Rose Yu 42 1 0 27 May 2024
AI-Lorenz: A physics-data-driven framework for black-box and gray-box identification of chaotic systems with symbolic regression Mario De Florio Ioannis G. Kevrekidis George Karniadakis 49 16 0 21 Dec 2023
Interpretable Neural PDE Solvers using Symbolic Frameworks Yolanne Yi Ran Lee AI4CE 32 0 0 31 Oct 2023
Correcting model misspecification in physics-informed neural networks (PINNs) Zongren Zou Xuhui Meng George Karniadakis PINN 29 41 0 16 Oct 2023
Coarse-Graining Hamiltonian Systems Using WSINDy Daniel Messenger J. Burby David M. Bortz 51 6 0 09 Oct 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 33 9 0 24 May 2023
Pseudo-Hamiltonian system identification Sigurd Holmsen Sølve Eidnes S. Riemer-Sørensen 18 3 0 09 May 2023
Mining Causality from Continuous-time Dynamics Models: An Application to Tsunami Forecasting Fan Wu Sanghyun Hong Dobsub Rim Noseong Park Kookjin Lee AI4TS 31 1 0 10 Oct 2022
Parameter-varying neural ordinary differential equations with partition-of-unity networks Kookjin Lee N. Trask 22 2 0 01 Oct 2022
Interpretable Polynomial Neural Ordinary Differential Equations Colby Fronk Linda R. Petzold 27 27 0 09 Aug 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces Sølve Eidnes Alexander J. Stasik Camilla Sterud Eivind Bøhn S. Riemer-Sørensen 22 17 0 06 Jun 2022
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 28 20 0 04 Mar 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 424 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 220 0 29 Sep 2019