Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning

10 July 2019

Jan Peters

Papers citing "Deep Lagrangian Networks: Using Physics as Model Prior for Deep Learning"

50 / 211 papers shown

Title
Bridging Active Exploration and Uncertainty-Aware Deployment Using Probabilistic Ensemble Neural Network Dynamics Taekyung Kim Jungwi Mun Junwon Seo Beomsu Kim S. Hong 34 11 0 20 May 2023
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 35 5 0 26 Apr 2023
Contingency Analyses with Warm Starter using Probabilistic Graphical Model Shimiao Li Amritanshu Pandey L. Pileggi AI4CE 23 2 0 10 Apr 2023
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning Daniel Palenicek M. Lutter João Carvalho Jan Peters 18 4 0 07 Mar 2023
Nature's Cost Function: Simulating Physics by Minimizing the Action Tim Strang Isabella Caruso S. Greydanus 16 3 0 03 Mar 2023
Modulated Neural ODEs I. Auzina Çağatay Yıldız Sara Magliacane Matthias Bethge E. Gavves 30 5 0 26 Feb 2023
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control Adam J. Thorpe Cyrus Neary Franck Djeumou Meeko Oishi Ufuk Topcu 30 7 0 09 Jan 2023
Towards Scalable Physically Consistent Neural Networks: an Application to Data-driven Multi-zone Thermal Building Models L. D. Natale B. Svetozarevic Philipp Heer Colin N. Jones AI4CE 23 28 0 23 Dec 2022
Physics-Informed Model-Based Reinforcement Learning Adithya Ramesh Balaraman Ravindran 19 10 0 05 Dec 2022
Guaranteed Conformance of Neurosymbolic Models to Natural Constraints Kaustubh Sridhar Souradeep Dutta James Weimer Insup Lee 19 7 0 02 Dec 2022
Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks Cyrus Neary Ufuk Topcu PINN AI4CE 11 12 0 01 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 25 18 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 18 12 0 29 Nov 2022
Hybrid Learning of Time-Series Inverse Dynamics Models for Locally Isotropic Robot Motion Tolga-Can Callar Sven Böttger 17 7 0 23 Nov 2022
Optimization-Based Control for Dynamic Legged Robots Patrick M. Wensing Michael Posa Yue Hu Adrien Escande Nicolas Mansard Andrea Del Prete 17 139 0 21 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 25 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
Port-metriplectic neural networks: thermodynamics-informed machine learning of complex physical systems Quercus Hernandez Alberto Badías Francisco Chinesta Elías Cueto PINN AI4CE 27 13 0 03 Nov 2022
Model-based Reinforcement Learning with a Hamiltonian Canonical ODE Network Yao Feng Yuhong Jiang Hang Su Dong Yan Jun Zhu 15 1 0 02 Nov 2022
Learning Modular Simulations for Homogeneous Systems Jayesh K. Gupta Sai H. Vemprala Ashish Kapoor 19 6 0 28 Oct 2022
Sample Efficient Dynamics Learning for Symmetrical Legged Robots:Leveraging Physics Invariance and Geometric Symmetries Jee-eun Lee Jaemin Lee T. Bandyopadhyay Luis Sentis DRL 27 2 0 13 Oct 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 30 11 0 11 Oct 2022
Learning Deep Nets for Gravitational Dynamics with Unknown Disturbance through Physical Knowledge Distillation: Initial Feasibility Study Hongbin Lin Qian Gao X. Chu Qi Dou Anton Deguet Peter Kazanzides K. W. S. Au AI4CE 28 7 0 04 Oct 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 28 17 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 38 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 27 19 0 22 Sep 2022
Clifford Neural Layers for PDE Modeling Johannes Brandstetter Rianne van den Berg Max Welling Jayesh K. Gupta AI4CE 60 80 0 08 Sep 2022
Learning the Dynamics of Particle-based Systems with Lagrangian Graph Neural Networks Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan PINN AI4CE 31 20 0 03 Sep 2022
From latent dynamics to meaningful representations Dedi Wang Yihang Wang Luke J. Evans P. Tiwary AI4CE 27 7 0 02 Sep 2022
Algorithmic Differentiation for Automated Modeling of Machine Learned Force Fields Niklas Schmitz Klaus-Robert Muller Stefan Chmiela AI4CE 19 11 0 25 Aug 2022
Constants of motion network M. F. Kasim Yi Heng Lim 23 4 0 22 Aug 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Multiscale Neural Operator: Learning Fast and Grid-independent PDE Solvers Björn Lütjens Catherine H. Crawford C. Watson C. Hill Dava Newman AI4CE 11 9 0 23 Jul 2022
Physics Embedded Neural Network Vehicle Model and Applications in Risk-Aware Autonomous Driving Using Latent Features Taekyung Kim Ho-Woon Lee Wonsuk Lee 6 17 0 16 Jul 2022
Complementing Brightness Constancy with Deep Networks for Optical Flow Prediction Vincent Le Guen Clément Rambour Nicolas Thome 16 1 0 08 Jul 2022
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 22 1 0 30 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
KeyCLD: Learning Constrained Lagrangian Dynamics in Keypoint Coordinates from Images Rembert Daems Jeroen Taets Francis Wyffels Guillaume Crevecoeur 11 1 0 22 Jun 2022
Recognition Models to Learn Dynamics from Partial Observations with Neural ODEs Mona Buisson-Fenet V. Morgenthaler Sebastian Trimpe F. D. Meglio 46 6 0 25 May 2022
Learning a Better Control Barrier Function Bolun Dai P. Krishnamurthy Farshad Khorrami 13 31 0 11 May 2022
AutoKE: An automatic knowledge embedding framework for scientific machine learning Mengge Du Yuntian Chen Dongxiao Zhang AI4CE 33 11 0 11 May 2022
Towards Practical Physics-Informed ML Design and Evaluation for Power Grid Shimiao Li Amritanshu Pandey L. Pileggi AI4CE 4 4 0 07 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
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 29 84 0 13 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 39 55 0 31 Mar 2022
Inferring Articulated Rigid Body Dynamics from RGBD Video Eric Heiden Ziang Liu Vibhav Vineet Erwin Coumans Gaurav Sukhatme PINN AI4CE 25 11 0 20 Mar 2022
Equivariant Graph Mechanics Networks with Constraints Wen-bing Huang J. Han Yu Rong Tingyang Xu Fuchun Sun Junzhou Huang AI4CE 33 79 0 12 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Real-time Model Predictive Control and System Identification Using Differentiable Physics Simulation Sirui Chen Keenon Werling A. Wu C. Karen Liu 17 6 0 20 Feb 2022