Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control

26 September 2019

Yaofeng Desmond Zhong

Papers citing "Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control"

50 / 170 papers shown

Title
Fast and Modular Whole-Body Lagrangian Dynamics of Legged Robots with Changing Morphology Sahand Farghdani Omar Abdelrahman Robin Chhabra 24 0 0 23 Apr 2025
Learning Nash Equilibrial Hamiltonian for Two-Player Collision-Avoiding Interactions Lei Zhang Siddharth Das Tanner Merry Wenlong Zhang Yi Ren 52 0 0 10 Mar 2025
ServoLNN: Lagrangian Neural Networks Driven by Servomechanisms Brandon Johns Zhuomin Zhou Elahe Abdi PINN 3DV 60 0 0 27 Feb 2025
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 42 0 0 12 Jan 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
Training Hamiltonian neural networks without backpropagation Atamert Rahma Chinmay Datar Felix Dietrich 62 0 0 26 Nov 2024
Projected Neural Differential Equations for Learning Constrained Dynamics Alistair J R White Anna Buttner Maximilian Gelbrecht Valentin Duruisseaux Niki Kilbertus Frank Hellmann Niklas Boers 39 0 0 31 Oct 2024
Identifiability Analysis of Linear ODE Systems with Hidden Confounders Yuanyuan Wang Biwei Huang Wei Huang Xi Geng Mingming Gong CML 30 0 0 29 Oct 2024
Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics? Tae-Geun Kim Seong Chan Park 23 0 0 28 Oct 2024
Learning dissipative Hamiltonian dynamics with reproducing kernel Hilbert spaces and random Fourier features Torbjørn Smith Olav Egeland 21 0 0 24 Oct 2024
Noether's razor: Learning Conserved Quantities Tycho F. A. van der Ouderaa Mark van der Wilk Pim de Haan 21 0 0 10 Oct 2024
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 33 1 0 04 Oct 2024
Response Estimation and System Identification of Dynamical Systems via Physics-Informed Neural Networks M. Haywood-Alexander Giacamo Arcieri A. Kamariotis Eleni Chatzi 28 1 0 02 Oct 2024
Learning Hamiltonian neural Koopman operator and simultaneously sustaining and discovering conservation law Jingdong Zhang Qunxi Zhu Wei Lin 30 8 0 04 Jun 2024
Neural Interaction Energy for Multi-Agent Trajectory Prediction Kaixin Shen Ruijie Quan Linchao Zhu Jun Xiao Yi Yang 32 0 0 25 Apr 2024
Functional Bilevel Optimization for Machine Learning Ieva Petrulionyte Julien Mairal Michael Arbel 39 2 0 29 Mar 2024
Improving Out-of-Distribution Generalization of Learned Dynamics by Learning Pseudometrics and Constraint Manifolds Yating Lin Glen Chou Dmitry Berenson OODD 33 0 0 18 Mar 2024
Unsupervised Learning of Hybrid Latent Dynamics: A Learn-to-Identify Framework Yubo Ye Sumeet Vadhavkar Xiajun Jiang R. Missel Huafeng Liu Linwei Wang 29 0 0 13 Mar 2024
Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control Wenhan Cao Wei Pan 28 0 0 27 Feb 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
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay A. Atanasov 23 10 0 17 Jan 2024
Learning of Hamiltonian Dynamics with Reproducing Kernel Hilbert Spaces Torbjorn Smith Olav Egeland 18 2 0 15 Dec 2023
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
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay AAML 35 22 0 10 Oct 2023
Hamiltonian Dynamics Learning from Point Cloud Observations for Nonholonomic Mobile Robot Control Abdullah Altawaitan Jason Stanley Sambaran Ghosal T. Duong Nikolay A. Atanasov 27 1 0 17 Sep 2023
Separable Hamiltonian Neural Networks Zi-Yu Khoo Dawen Wu Jonathan Sze Choong Low Stéphane Bressan 15 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 33 2 0 26 Aug 2023
Learning to Predict 3D Rotational Dynamics from Images of a Rigid Body with Unknown Mass Distribution J. Mason Christine Allen-Blanchette Nicholas Zolman Elizabeth Davison Naomi Leonard 3DH 25 2 0 24 Aug 2023
Hamiltonian GAN Christine Allen-Blanchette GAN AI4CE 25 1 0 22 Aug 2023
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems Truong X. Nghiem Ján Drgoňa Colin N. Jones Zoltán Nagy Roland Schwan ... J. Paulson Andrea Carron M. Zeilinger Wenceslao Shaw-Cortez D. Vrabie PINN AI4CE 32 30 0 24 Jun 2023
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers Kai Lagemann C. Lagemann Swarnava Mukherjee 34 2 0 21 Jun 2023
Graph Neural Stochastic Differential Equations for Learning Brownian Dynamics S. Bishnoi J. Jayadeva Sayan Ranu N. M. A. Krishnan 22 3 0 20 Jun 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair J R White Niki Kilbertus Maximilian Gelbrecht Niklas Boers 20 6 0 16 Jun 2023
Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Wee Peng Tay 19 12 0 30 May 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
Neural Lyapunov and Optimal Control Daniel Layeghi Steve Tonneau M. Mistry 16 0 0 24 May 2023
Uncertainty and Structure in Neural Ordinary Differential Equations Katharina Ott Michael Tiemann Philipp Hennig AI4CE 26 5 0 22 May 2023
RDA-INR: Riemannian Diffeomorphic Autoencoding via Implicit Neural Representations Sven Dummer N. Strisciuglio Christoph Brune MedIm 21 2 0 22 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 27 3 0 02 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Learning Energy Conserving Dynamics Efficiently with Hamiltonian Gaussian Processes M. Ross Markus Heinonen 8 2 0 03 Mar 2023
Node Embedding from Hamiltonian Information Propagation in Graph Neural Networks Qiyu Kang Kai Zhao Yang Song Sijie Wang Rui She Wee Peng Tay 35 0 0 02 Mar 2023
Modulated Neural ODEs I. Auzina Çağatay Yıldız Sara Magliacane Matthias Bethge E. Gavves 25 5 0 26 Feb 2023
Neural Laplace Control for Continuous-time Delayed Systems Samuel Holt Alihan Huyuk Zhaozhi Qian Hao Sun M. Schaar OffRL 21 10 0 24 Feb 2023
Geometric Clifford Algebra Networks David Ruhe Jayesh K. Gupta Steven De Keninck Max Welling Johannes Brandstetter AI4CE 18 33 0 13 Feb 2023
Learning Control-Oriented Dynamical Structure from Data Spencer M. Richards Jean-Jacques E. Slotine Navid Azizan Marco Pavone 18 6 0 06 Feb 2023
Hamiltonian Neural Networks with Automatic Symmetry Detection Eva Dierkes Christian Offen Sina Ober-Blobaum K. Flaßkamp 17 7 0 19 Jan 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control Adam J. Thorpe Cyrus Neary Franck Djeumou Meeko Oishi Ufuk Topcu 30 7 0 09 Jan 2023
Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators Yannik P. Wotte Sven Dummer N. Botteghi C. Brune Stefano Stramigioli Federico Califano 20 5 0 29 Dec 2022