Symplectic Recurrent Neural Networks

29 September 2019

Papers citing "Symplectic Recurrent Neural Networks"

50 / 59 papers shown

Title
Efficiently Parameterized Neural Metriplectic Systems Anthony Gruber Kookjin Lee Haksoo Lim Noseong Park Nathaniel Trask 65 1 0 28 Jan 2025
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery Yana Lishkova P. Scherer Steffen Ridderbusch M. Jamnik Pietro Lio' Sina Ober-Blobaum Christian Offen PINN 70 7 0 28 Jan 2025
Bayesian identification of nonseparable Hamiltonians with multiplicative noise using deep learning and reduced-order modeling Nicholas Galioto Harsh Sharma Boris Kramer Alex Arkady Gorodetsky 44 0 0 23 Jan 2024
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay Atanasov 28 10 0 17 Jan 2024
Adversarial Robustness in Graph Neural Networks: A Hamiltonian Approach Kai Zhao Qiyu Kang Yang Song Rui She Sijie Wang Wee Peng Tay AAML 40 22 0 10 Oct 2023
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 31 1 0 06 Sep 2023
Hamiltonian GAN Christine Allen-Blanchette GAN AI4CE 40 1 0 22 Aug 2023
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators Haakon Noren Sølve Eidnes E. Celledoni 21 3 0 06 Jun 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 20 10 0 27 Apr 2023
Constraining Chaos: Enforcing dynamical invariants in the training of recurrent neural networks Jason A. Platt S. Penny T. A. Smith Tse-Chun Chen H. Abarbanel AI4TS 36 5 0 24 Apr 2023
Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods Haakon Noren 24 3 0 07 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
Learning PDE Solution Operator for Continuous Modeling of Time-Series Yesom Park Jaemoo Choi Changyeon Yoon Changhoon Song Myung-joo Kang AI4TS AI4CE 27 3 0 02 Feb 2023
AirfRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged Navier-Stokes Solutions F. Bonnet Jocelyn Ahmed Mazari Paola Cinnella Patrick Gallinari AI4CE 33 54 0 15 Dec 2022
Lie Group Forced Variational Integrator Networks for Learning and Control of Robot Systems Valentin Duruisseaux T. Duong Melvin Leok Nikolay Atanasov DRL AI4CE 29 12 0 29 Nov 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
Thermodynamics-informed neural networks for physically realistic mixed reality Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 22 16 0 24 Oct 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 30 11 0 11 Oct 2022
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 40 10 0 05 Oct 2022
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 41 12 0 23 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 46 8 0 23 Sep 2022
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models Harsh Sharma Nicholas Galioto Alex A. Gorodetsky Boris Kramer 38 3 0 15 Sep 2022
Constants of motion network M. F. Kasim Yi Heng Lim 34 4 0 22 Aug 2022
Estimating a potential without the agony of the partition function E. Haber Moshe Eliasof L. Tenorio 33 2 0 19 Aug 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Tractable Dendritic RNNs for Reconstructing Nonlinear Dynamical Systems Manuela Brenner Florian Hess Jonas M. Mikhaeil Leonard Bereska Zahra Monfared Po-Chen Kuo Daniel Durstewitz AI4CE 37 29 0 06 Jul 2022
Learning Geometrically Disentangled Representations of Protein Folding Simulations N. Joseph Tatro Payel Das Pin-Yu Chen Vijil Chenthamarakshan Rongjie Lai AI4CE 17 0 0 20 May 2022
VPNets: Volume-preserving neural networks for learning source-free dynamics Aiqing Zhu Beibei Zhu Jiawei Zhang Yifa Tang Jian-Dong Liu 34 3 0 29 Apr 2022
STONet: A Neural-Operator-Driven Spatio-temporal Network Haitao Lin Guojiang Zhao Lirong Wu Stan Z. Li AI4TS AI4CE 15 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 32 84 0 13 Apr 2022
Thermodynamics-informed graph neural networks Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto AI4CE PINN 32 31 0 03 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Learning continuous models for continuous physics Aditi S. Krishnapriyan A. Queiruga N. Benjamin Erichson Michael W. Mahoney AI4CE 24 33 0 17 Feb 2022
Deconstructing the Inductive Biases of Hamiltonian Neural Networks Nate Gruver Marc Finzi Samuel Stanton A. Wilson AI4CE 23 39 0 10 Feb 2022
Learning Hamiltonians of constrained mechanical systems E. Celledoni A. Leone Davide Murari B. Owren AI4CE 44 17 0 31 Jan 2022
Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately A. Sosanya S. Greydanus PINN AI4CE 44 27 0 25 Jan 2022
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning Saul Santos Monica Ekal R. Ventura 32 5 0 20 Jan 2022
Constraint-based graph network simulator Yulia Rubanova Alvaro Sanchez-Gonzalez Tobias Pfaff Peter W. Battaglia PINN AI4CE 32 28 0 16 Dec 2021
Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks Tian Zheng Weihao Gao Chong-Jun Wang AI4CE 36 3 0 30 Nov 2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 42 8 0 10 Nov 2021
Which priors matter? Benchmarking models for learning latent dynamics Aleksandar Botev Andrew Jaegle Peter Wirnsberger Daniel Hennes I. Higgins AI4CE 32 28 0 09 Nov 2021
Locally-symplectic neural networks for learning volume-preserving dynamics J. Bajārs 32 9 0 19 Sep 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 32 25 0 11 Sep 2021
An Extensible Benchmark Suite for Learning to Simulate Physical Systems Karl Otness Arvi Gjoka Joan Bruna Daniele Panozzo Benjamin Peherstorfer T. Schneider Denis Zorin 24 23 0 09 Aug 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 44 42 0 23 Jun 2021
Symplectic Learning for Hamiltonian Neural Networks M. David Florian Méhats 24 34 0 22 Jun 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 30 25 0 25 Feb 2021
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory Takashi Matsubara Yuto Miyatake Takaharu Yaguchi 20 23 0 19 Feb 2021
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty 52 34 0 12 Feb 2021