Lagrangian Neural Networks

10 March 2020

Papers citing "Lagrangian Neural Networks"

50 / 103 papers shown

Title
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 22 1 0 30 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 32 25 0 29 May 2022
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 24 118 0 29 May 2022
Leveraging Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations Maximilian Mueller Robin Greif Frank Jenko Nils Thuerey 24 3 0 02 May 2022
Neural Implicit Representations for Physical Parameter Inference from a Single Video Florian Hofherr Lukas Koestler Florian Bernard Daniel Cremers AI4CE 37 9 0 29 Apr 2022
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations Fang Wu Stan Z. Li DiffM 26 31 0 19 Apr 2022
A posteriori learning for quasi-geostrophic turbulence parametrization Hugo Frezat Julien Le Sommer Ronan Fablet G. Balarac Redouane Lguensat 27 56 0 08 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 42 57 0 31 Mar 2022
Investigating Compounding Prediction Errors in Learned Dynamics Models Nathan Lambert K. Pister Roberto Calandra AI4CE 14 27 0 17 Mar 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 18 4 0 14 Feb 2022
Robust Hybrid Learning With Expert Augmentation Antoine Wehenkel Jens Behrmann Hsiang Hsu Guillermo Sapiro Gilles Louppe and J. Jacobsen 26 8 0 08 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
Taylor-Lagrange Neural Ordinary Differential Equations: Toward Fast Training and Evaluation of Neural ODEs Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu AI4TS 30 18 0 14 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
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 73 26 0 06 Dec 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 29 3 0 25 Nov 2021
Physics-enhanced Neural Networks in the Small Data Regime Jonas Eichelsdörfer Sebastian Kaltenbach P. Koutsourelakis AI4CE PINN 14 5 0 19 Nov 2021
Climate Modeling with Neural Diffusion Equations JeeHyun Hwang Jeongwhan Choi Hwan-Kyu Choi Kookjin Lee Dongeun Lee Noseong Park DiffM 24 22 0 11 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
On the Stochastic Stability of Deep Markov Models Ján Drgoňa Sayak Mukherjee Jiaxin Zhang Frank Liu M. Halappanavar BDL 19 5 0 08 Nov 2021
Constructing Neural Network-Based Models for Simulating Dynamical Systems Christian Møldrup Legaard Thomas Schranz G. Schweiger Ján Drgovna Basak Falay C. Gomes Alexandros Iosifidis M. Abkar P. Larsen PINN AI4CE 33 93 0 02 Nov 2021
A Differentiable Newton-Euler Algorithm for Real-World Robotics M. Lutter Vallijah Subasri Joe Watson Frank Rudzicz 24 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
Lagrangian Neural Network with Differentiable Symmetries and Relational Inductive Bias Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 47 4 0 07 Oct 2021
Neural Network Verification in Control M. Everett AAML 34 16 0 30 Sep 2021
Physics-Augmented Learning: A New Paradigm Beyond Physics-Informed Learning Ziming Liu Yunyue Chen Yuanqi Du Max Tegmark PINN AI4CE 40 22 0 28 Sep 2021
Machine-learning hidden symmetries Ziming Liu Max Tegmark 48 52 0 20 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
Characterizing possible failure modes in physics-informed neural networks Aditi S. Krishnapriyan A. Gholami Shandian Zhe Robert M. Kirby Michael W. Mahoney PINN AI4CE 33 610 0 02 Sep 2021
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems Shaan Desai M. Mattheakis David Sondak P. Protopapas Stephen J. Roberts AI4CE 30 43 0 16 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 39 64 0 02 Jul 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
Stateful ODE-Nets using Basis Function Expansions A. Queiruga N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 27 16 0 21 Jun 2021
Scalars are universal: Equivariant machine learning, structured like classical physics Soledad Villar D. Hogg Kate Storey-Fisher Weichi Yao Ben Blum-Smith PINN AI4CE 24 130 0 11 Jun 2021
GEM: Group Enhanced Model for Learning Dynamical Control Systems Philippe Hansen-Estruch Wenling Shang Lerrel Pinto Pieter Abbeel Stas Tiomkin AI4CE 27 2 0 07 Apr 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 30 25 0 25 Feb 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi Alexandros Kalousis DRL AI4CE 30 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
Meta-Learning Dynamics Forecasting Using Task Inference Rui Wang Robin G. Walters Rose Yu OOD AI4TS AI4CE 24 31 0 20 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
Neural Dynamic Policies for End-to-End Sensorimotor Learning Shikhar Bahl Mustafa Mukadam Abhinav Gupta Deepak Pathak 13 83 0 04 Dec 2020
Dissipative Deep Neural Dynamical Systems Ján Drgoňa Soumya Vasisht Aaron Tuor D. Vrabie 21 7 0 26 Nov 2020
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
Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting Yuan Yin Vincent Le Guen Jérémie Donà Emmanuel de Bézenac Ibrahim Ayed Nicolas Thome Patrick Gallinari AI4CE PINN 30 132 0 09 Oct 2020
TorchDyn: A Neural Differential Equations Library Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 19 24 0 20 Sep 2020
Interpretable Sequence Learning for COVID-19 Forecasting Sercan Ö. Arik Chun-Liang Li Jinsung Yoon Rajarishi Sinha Arkady Epshteyn ... Martin Nikoltchev Yash Sonthalia Hootan Nakhost Elli Kanal Tomas Pfister AI4TS 20 83 0 03 Aug 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 41 25 0 23 Jun 2020
Lipschitz Recurrent Neural Networks N. Benjamin Erichson Omri Azencot A. Queiruga Liam Hodgkinson Michael W. Mahoney 30 107 0 22 Jun 2020