Variational Integrator Networks for Physically Structured Embeddings

21 October 2019

Papers citing "Variational Integrator Networks for Physically Structured Embeddings"

21 / 21 papers shown

Title
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery Yana Lishkova P. Scherer Steffen Ridderbusch M. Jamnik Pietro Lio Sina Ober-Blobaum Christian Offen PINN 73 7 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 100 1 0 22 Jan 2025
Online Control-Informed Learning Zihao Liang Tianyu Zhou Zehui Lu Shaoshuai Mou 38 1 0 04 Oct 2024
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
Hamiltonian GAN Christine Allen-Blanchette GAN AI4CE 40 1 0 22 Aug 2023
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning Yeongwoo Song Hawoong Jeong OOD AI4CE 24 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 31 12 0 29 Nov 2022
Guaranteed Conservation of Momentum for Learning Particle-based Fluid Dynamics L. Prantl Benjamin Ummenhofer V. Koltun Nils Thuerey AI4CE PINN 26 29 0 12 Oct 2022
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks Valentin Duruisseaux J. Burby Q. Tang 43 11 0 11 Oct 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 37 84 0 13 Apr 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 31 15 0 28 Feb 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
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 50 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 40 28 0 09 Nov 2021
A Differentiable Newton-Euler Algorithm for Real-World Robotics M. Lutter Vallijah Subasri Joe Watson Frank Rudzicz 29 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 27 58 0 21 Oct 2021
Combining Physics and Deep Learning to learn Continuous-Time Dynamics Models M. Lutter Jan Peters PINN AI4CE 43 39 0 05 Oct 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi Alexandros Kalousis DRL AI4CE 40 54 0 25 Feb 2021
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 19 16 0 22 Feb 2021
Differentiable Physics Models for Real-world Offline Model-based Reinforcement Learning M. Lutter Johannes Silberbauer Joe Watson Jan Peters OffRL 29 33 0 03 Nov 2020
LagNetViP: A Lagrangian Neural Network for Video Prediction Christine Allen-Blanchette Sushant Veer Anirudha Majumdar Naomi Ehrich Leonard 44 30 0 24 Oct 2020