Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems

16 July 2021

Papers citing "Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems"

31 / 31 papers shown

Title
Stable Port-Hamiltonian Neural Networks Fabian J. Roth Dominik K. Klein Maximilian Kannapinn Jan Peters Oliver Weeger 72 1 0 04 Feb 2025
Symplectic Neural Flows for Modeling and Discovery Priscilla Canizares Davide Murari Carola-Bibiane Schönlieb Ferdia Sherry Zakhar Shumaylov 80 1 0 21 Dec 2024
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 77 1 0 15 Dec 2024
Training Hamiltonian neural networks without backpropagation Atamert Rahma Chinmay Datar Felix Dietrich 69 0 0 26 Nov 2024
Human-Robot Cooperative Distribution Coupling for Hamiltonian-Constrained Social Navigation Weizheng Wang Chao Yu Yu Wang Byung-Cheol Min 144 2 0 20 Sep 2024
Data-driven identification of latent port-Hamiltonian systems J. Rettberg Jonas Kneifl Julius Herb Patrick Buchfink Jörg Fehr B. Haasdonk PINN 26 2 0 15 Aug 2024
Physics-Constrained Learning for PDE Systems with Uncertainty Quantified Port-Hamiltonian Models Kaiyuan Tan Peilun Li Thomas Beckers AI4CE 18 3 0 17 Jun 2024
Predicting Ship Responses in Different Seaways using a Generalizable Force Correcting Machine Learning Method K. Marlantes P. Bandyk Kevin J. Maki 19 3 0 13 May 2024
Neural Operators Meet Energy-based Theory: Operator Learning for Hamiltonian and Dissipative PDEs Yusuke Tanaka Takaharu Yaguchi Tomoharu Iwata N. Ueda AI4CE 37 0 0 14 Feb 2024
Discussing the Spectrum of Physics-Enhanced Machine Learning; a Survey on Structural Mechanics Applications M. Haywood-Alexander Wei Liu Kiran Bacsa Zhilu Lai Eleni Chatzi AI4CE 13 9 0 31 Oct 2023
Separable Hamiltonian Neural Networks Zi-Yu Khoo Dawen Wu Jonathan Sze Choong Low Stéphane Bressan 20 1 0 03 Sep 2023
Deep Learning for Structure-Preserving Universal Stable Koopman-Inspired Embeddings for Nonlinear Canonical Hamiltonian Dynamics P. Goyal Süleyman Yıldız P. Benner 36 2 0 26 Aug 2023
How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations Franck Djeumou Cyrus Neary Ufuk Topcu DiffM 24 8 0 10 Jun 2023
Reversible and irreversible bracket-based dynamics for deep graph neural networks A. Gruber Kookjin Lee N. Trask AI4CE 25 9 0 24 May 2023
Learning Switching Port-Hamiltonian Systems with Uncertainty Quantification Thomas Beckers Tom Z. Jiahao George J. Pappas 31 2 0 15 May 2023
Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior Thomas Beckers Jacob H. Seidman P. Perdikaris George J. Pappas PINN 24 17 0 15 May 2023
Pseudo-Hamiltonian system identification Sigurd Holmsen Sølve Eidnes S. Riemer-Sørensen 18 3 0 09 May 2023
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models Sarvin Moradi N. Jaensson Roland Tóth Maarten Schoukens PINN 30 3 0 02 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks Cyrus Neary Ufuk Topcu PINN AI4CE 13 12 0 01 Dec 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Pseudo-Hamiltonian Neural Networks with State-Dependent External Forces Sølve Eidnes Alexander J. Stasik Camilla Sterud Eivind Bøhn S. Riemer-Sørensen 11 17 0 06 Jun 2022
Learning reversible symplectic dynamics Riccardo Valperga K. Webster Victoria G Klein D. Turaev J. Lamb AI4CE 9 13 0 26 Apr 2022
Thermodynamics-informed graph neural networks Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto AI4CE PINN 27 31 0 03 Mar 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 15 39 0 10 Feb 2022
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 70 26 0 06 Dec 2021
One-Shot Transfer Learning of Physics-Informed Neural Networks Shaan Desai M. Mattheakis H. Joy P. Protopapas Stephen J. Roberts PINN AI4CE 16 58 0 21 Oct 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 32 24 0 11 Sep 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Hamiltonian neural networks for solving equations of motion M. Mattheakis David Sondak Akshunna S. Dogra P. Protopapas 19 56 0 29 Jan 2020
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 280 1,400 0 01 Dec 2016