Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control

26 September 2019

Yaofeng Desmond Zhong

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

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Title
Likelihood-based generalization of Markov parameter estimation and multiple shooting objectives in system identification Nicholas Galioto Alex Arkady Gorodetsky 26 1 0 20 Dec 2022
Physics-Informed Model-Based Reinforcement Learning Adithya Ramesh Balaraman Ravindran 13 10 0 05 Dec 2022
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints Kaustubh Sridhar Souradeep Dutta James Weimer Insup Lee 17 7 0 02 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 22 17 0 30 Nov 2022
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux T. Duong Melvin Leok Nikolay A. Atanasov DRL AI4CE 10 11 0 29 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 23 89 0 15 Nov 2022
Unravelling the Performance of Physics-informed Graph Neural Networks for Dynamical Systems A. Thangamuthu Gunjan Kumar S. Bishnoi Ravinder Bhattoo N. M. A. Krishnan Sayan Ranu AI4CE PINN 32 22 0 10 Nov 2022
ODEs learn to walk: ODE-Net based data-driven modeling for crowd dynamics Chen Cheng Jinglai Li 19 0 0 18 Oct 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 28 11 0 11 Oct 2022
FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities Takashi Matsubara Takaharu Yaguchi PINN 14 7 0 01 Oct 2022
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian Oswin So Gongjie Li Evangelos A. Theodorou Molei Tao AI4CE 15 3 0 30 Sep 2022
Learning Interpretable Dynamics from Images of a Freely Rotating 3D Rigid Body J. Mason Christine Allen-Blanchette Nicholas Zolman Elizabeth Davison Naomi Ehrich Leonard 3DH AI4CE 33 8 0 23 Sep 2022
Enhancing the Inductive Biases of Graph Neural ODE for Modeling Dynamical Systems S. Bishnoi Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 18 19 0 22 Sep 2022
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference Somayajulu L. N. Dhulipala Yifeng Che Michael D. Shields 30 0 0 19 Sep 2022
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models Harsh Sharma Nicholas Galioto Alex A. Gorodetsky Boris Kramer 30 3 0 15 Sep 2022
Constants of motion network M. F. Kasim Yi Heng Lim 12 4 0 22 Aug 2022
Bayesian Inference with Latent Hamiltonian Neural Networks Somayajulu L. N. Dhulipala Yifeng Che Michael D. Shields BDL 31 3 0 12 Aug 2022
Robust and Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics Zhichao Li T. Duong Nikolay A. Atanasov 11 1 0 22 Jul 2022
Human Trajectory Prediction via Neural Social Physics Jiangbei Yue Dinesh Manocha He-Nan Wang AI4CE 19 100 0 21 Jul 2022
Learning Deep Input-Output Stable Dynamics Yuji Okamoto Ryosuke Kojima OOD 23 5 0 27 Jun 2022
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias Yupu Lu Shi-Min Lin Guanqi Chen Jia-Yu Pan 32 7 0 24 Jun 2022
Noisy Learning for Neural ODEs Acts as a Robustness Locus Widening Martin Gonzalez H. Hajri Loic Cantat M. Petreczky 27 1 0 16 Jun 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
Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs Mona Buisson-Fenet V. Morgenthaler Sebastian Trimpe F. D. Meglio 43 6 0 25 May 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video Florian Hofherr Lukas Koestler Florian Bernard Daniel Cremers AI4CE 34 9 0 29 Apr 2022
VPNets: Volume-preserving neural networks for learning source-free dynamics Aiqing Zhu Beibei Zhu Jiawei Zhang Yifa Tang Jian-Dong Liu 26 3 0 29 Apr 2022
Continuous-time identification of dynamic state-space models by deep subspace encoding G. Beintema Maarten Schoukens R. Tóth 15 11 0 20 Apr 2022
A dynamical systems based framework for dimension reduction Ryeongkyung Yoon Braxton Osting 11 1 0 18 Apr 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 27 84 0 13 Apr 2022
Learning Trajectories of Hamiltonian Systems with Neural Networks Katsiaryna Haitsiukevich Alexander Ilin 17 4 0 11 Apr 2022
MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems Jiahao Zhang Shiqi Zhang Guang Lin 10 13 0 07 Apr 2022
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning Chuizheng Meng Sungyong Seo Defu Cao Sam Griesemer Yan Liu PINN AI4CE 34 55 0 31 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 25 22 0 28 Feb 2022
Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits Alan Yang J. Xiong Maxim Raginsky E. Rosenbaum AI4TS 16 4 0 14 Feb 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 13 39 0 10 Feb 2022
Spectrally Adapted Physics-Informed Neural Networks for Solving Unbounded Domain Problems Mingtao Xia Lucas Böttcher T. Chou 16 19 0 06 Feb 2022
Learning Hamiltonians of constrained mechanical systems E. Celledoni A. Leone Davide Murari B. Owren AI4CE 36 17 0 31 Jan 2022
Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately A. Sosanya S. Greydanus PINN AI4CE 35 26 0 25 Jan 2022
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning Saul Santos Monica Ekal R. Ventura 19 5 0 20 Jan 2022
Control of Dual-Sourcing Inventory Systems using Recurrent Neural Networks Lucas Böttcher Thomas Asikis I. Fragkos BDL 11 10 0 16 Jan 2022
Physics-guided Learning-based Adaptive Control on the SE(3) Manifold T. Duong Nikolay A. Atanasov PINN DRL AI4CE 31 0 0 12 Jan 2022
Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics Zhichao Li T. Duong Nikolay A. Atanasov 13 2 0 09 Dec 2021
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 65 26 0 06 Dec 2021
Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks Tian Zheng Weihao Gao Chong-Jun Wang AI4CE 21 3 0 30 Nov 2021
Neural Symplectic Integrator with Hamiltonian Inductive Bias for the Gravitational $N$ -body Problem Maxwell X. Cai Simon Portegies Zwart Damian Podareanu PINN 20 3 0 28 Nov 2021
Towards Conditional Generation of Minimal Action Potential Pathways for Molecular Dynamics J. Cava J. Vant Nicholas Ho Ankita Shulka P. Turaga Ross Maciejewski A. Singharoy AI4CE 20 2 0 28 Nov 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 21 3 0 25 Nov 2021
Physics-informed neural networks via stochastic Hamiltonian dynamics learning Chandrajit L. Bajaj Minh Nguyen 11 1 0 15 Nov 2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 37 7 0 10 Nov 2021