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Variational Integrator Networks for Physically Structured Embeddings

21 October 2019

Papers citing "Variational Integrator Networks for Physically Structured Embeddings"

30 / 30 papers shown

Title
Four Principles for Physically Interpretable World Models Jordan Peper Zhenjiang Mao Yuang Geng Siyuan Pan Ivan Ruchkin 145 1 0 04 Mar 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 118 8 0 28 Jan 2025
AnyNav: Visual Neuro-Symbolic Friction Learning for Off-road Navigation Taimeng Fu Zitong Zhan Zhipeng Zhao Shaoshu Su Xiao Lin Ehsan Esfahani Karthik Dantu Souma Chowdhury Chen Wang 144 2 0 22 Jan 2025
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 122 1 0 04 Oct 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 48 12 0 31 Oct 2023
Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients Marc Härkönen Markus Lange-Hegermann Bogdan Raiță 140 16 0 29 Dec 2022
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning Yeongwoo Song Hawoong Jeong OOD AI4CE 80 1 0 02 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 116 13 0 29 Nov 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 75 11 0 11 Oct 2022
Symplectically Integrated Symbolic Regression of Hamiltonian Dynamical Systems Daniel M. DiPietro Bo Zhu 28 1 0 04 Sep 2022
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images Rembert Daems Jeroen Taets Francis Wyffels Guillaume Crevecoeur 65 1 0 22 Jun 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 71 91 0 13 Apr 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 73 16 0 28 Feb 2022
Symplectic Momentum Neural Networks -- Using Discrete Variational Mechanics as a prior in Deep Learning Saul Santos Monica Ekal R. Ventura 63 5 0 20 Jan 2022
Structure-Preserving Learning Using Gaussian Processes and Variational Integrators Jan Brüdigam Martin Schuck A. Capone Stefan Sosnowski Sandra Hirche 82 4 0 10 Dec 2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 89 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 119 28 0 09 Nov 2021
A Differentiable Newton-Euler Algorithm for Real-World Robotics M. Lutter Vallijah Subasri Joe Watson Frank Rudzicz 80 7 0 24 Oct 2021
One-Shot Transfer Learning of Physics-Informed Neural Networks Shaan Desai M. Mattheakis H. Joy P. Protopapas Stephen J. Roberts PINN AI4CE 88 58 0 21 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 97 42 0 05 Oct 2021
Forced Variational Integrator Networks for Prediction and Control of Mechanical Systems Aaron J. Havens Girish Chowdhary PINN OOD AI4CE 61 8 0 05 Jun 2021
Physical Constraint Embedded Neural Networks for inference and noise regulation Gregory Barber Mulugeta Haile Tzikang Chen PINN 22 1 0 19 May 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi Alexandros Kalousis DRL AI4CE 96 56 0 25 Feb 2021
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 75 16 0 22 Feb 2021
Structure-preserving Gaussian Process Dynamics K. Ensinger Friedrich Solowjow Sebastian Ziesche Michael Tiemann Sebastian Trimpe 73 9 0 02 Feb 2021
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning M. Lutter Johannes Silberbauer Joe Watson Jan Peters OffRL 90 34 0 03 Nov 2020
LagNetViP: A Lagrangian Neural Network for Video Prediction Christine Allen-Blanchette Sushant Veer Anirudha Majumdar Naomi Ehrich Leonard 103 31 0 24 Oct 2020
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control Yaofeng Desmond Zhong Naomi Ehrich Leonard DRL AI4CE 95 43 0 03 Jul 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 88 31 0 10 Jun 2020
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework Wanxin Jin Zhaoran Wang Zhuoran Yang Shaoshuai Mou 96 80 0 30 Dec 2019