Lagrangian Neural Networks

10 March 2020

Papers citing "Lagrangian Neural Networks"

50 / 93 papers shown

Title
Learning and Transferring Physical Models through Derivatives Alessandro Trenta Andrea Cossu Davide Bacciu AI4CE 34 0 0 02 May 2025
Provably-Safe, Online System Identification Bohao Zhang Zichang Zhou Ram Vasudevan 43 0 0 30 Apr 2025
Learned Perceptive Forward Dynamics Model for Safe and Platform-aware Robotic Navigation Pascal Roth Jonas Frey César Cadena Marco Hutter 28 0 0 27 Apr 2025
New Recipe for Semi-supervised Community Detection: Clique Annealing under Crystallization Kinetics Ling Cheng Jiashu Pu Ruicheng Liang Qian Shao Hezhe Qiao Feida Zhu 31 0 0 22 Apr 2025
Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks Z. Liu Xiaoda Wang Bohan Wang Zijie Huang Carl Yang Wei-dong Jin AI4TS AI4CE 131 1 0 29 Mar 2025
MetaSym: A Symplectic Meta-learning Framework for Physical Intelligence Pranav Vaidhyanathan Aristotelis Papatheodorou Mark T. Mitchison Natalia Ares Ioannis Havoutis PINN AI4CE 33 1 0 23 Feb 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 63 7 0 28 Jan 2025
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics Katharina Friedl Noémie Jaquier Jens Lundell Tamim Asfour Danica Kragic AI4CE 26 0 0 24 Oct 2024
Efficient, Accurate and Stable Gradients for Neural ODEs Sam McCallum James Foster 32 4 0 15 Oct 2024
Feedback Favors the Generalization of Neural ODEs Jindou Jia Zihan Yang Meng Wang Kexin Guo Jianfei Yang Xiang Yu Lei Guo OOD AI4CE 35 2 0 14 Oct 2024
Transport-Embedded Neural Architecture: Redefining the Landscape of physics aware neural models in fluid mechanics Amirmahdi Jafari 26 0 0 05 Oct 2024
Learning Physics From Video: Unsupervised Physical Parameter Estimation for Continuous Dynamical Systems Alejandro Castañeda Garcia J. C. V. Gemert Daan Brinks Nergis Tömen 36 0 0 02 Oct 2024
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Anselm Paulus Georg Martius Vít Musil AI4CE 47 1 0 08 Jul 2024
Closure Discovery for Coarse-Grained Partial Differential Equations Using Grid-based Reinforcement Learning Jan-Philipp von Bassewitz Sebastian Kaltenbach P. Koumoutsakos AI4CE 30 1 0 01 Feb 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 36 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 A. Atanasov 23 10 0 17 Jan 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 24 8 0 29 Dec 2023
Neural Autoencoder-Based Structure-Preserving Model Order Reduction and Control Design for High-Dimensional Physical Systems Marco Lepri Davide Bacciu Cosimo Della Santina AI4CE 33 8 0 11 Dec 2023
Pseudo-rigid body networks: learning interpretable deformable object dynamics from partial observations Shamil Mamedov A. R. Geist Jan Swevers Sebastian Trimpe AI4CE 16 2 0 16 Jul 2023
Discovering Symbolic Laws Directly from Trajectories with Hamiltonian Graph Neural Networks S. Bishnoi Ravinder Bhattoo J. Jayadeva Sayan Ranu N. M. A. Krishnan PINN AI4CE 31 1 0 11 Jul 2023
Learning Latent Dynamics via Invariant Decomposition and (Spatio-)Temporal Transformers Kai Lagemann C. Lagemann Swarnava Mukherjee 34 2 0 21 Jun 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 30 28 0 29 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 18 10 0 27 Apr 2023
Machine Learning for Partial Differential Equations Steven L. Brunton J. Nathan Kutz AI4CE 32 20 0 30 Mar 2023
The transformative potential of machine learning for experiments in fluid mechanics Ricardo Vinuesa Steven L. Brunton B. McKeon AI4CE 19 68 0 28 Mar 2023
MetaPhysiCa: OOD Robustness in Physics-informed Machine Learning S Chandra Mouli M. A. Alam Bruno Ribeiro OOD 26 4 0 06 Mar 2023
Nature's Cost Function: Simulating Physics by Minimizing the Action Tim Strang Isabella Caruso S. Greydanus 11 3 0 03 Mar 2023
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles Roy T. Forestano Konstantin T. Matchev Katia Matcheva Alexander Roman Eyup B. Unlu Sarunas Verner AI4CE 28 21 0 13 Jan 2023
Discovering Efficient Periodic Behaviours in Mechanical Systems via Neural Approximators Yannik P. Wotte Sven Dummer N. Botteghi C. Brune Stefano Stramigioli Federico Califano 20 5 0 29 Dec 2022
Knowledge-augmented Deep Learning and Its Applications: A Survey Zijun Cui Tian Gao Kartik Talamadupula Qiang Ji 22 17 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 8 11 0 29 Nov 2022
Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations Simon Koop M. Peletier J. Portegies Vlado Menkovski DiffM 22 1 0 17 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 48 0 14 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
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems Daniel Kelshaw Georgios Rigas Luca Magri AI4CE 21 17 0 31 Oct 2022
Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective Tanya Marwah Zachary Chase Lipton Jianfeng Lu Andrej Risteski 41 10 0 21 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 28 11 0 11 Oct 2022
Exact conservation laws for neural network integrators of dynamical systems E. Müller PINN 39 12 0 23 Sep 2022
Learning Articulated Rigid Body Dynamics with Lagrangian Graph Neural Network Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan AI4CE 26 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 33 8 0 23 Sep 2022
Continuous MDP Homomorphisms and Homomorphic Policy Gradient S. Rezaei-Shoshtari Rosie Zhao Prakash Panangaden D. Meger Doina Precup 31 18 0 15 Sep 2022
Learning the Dynamics of Particle-based Systems with Lagrangian Graph Neural Networks Ravinder Bhattoo Sayan Ranu N. M. A. Krishnan PINN AI4CE 23 20 0 03 Sep 2022
Constants of motion network M. F. Kasim Yi Heng Lim 10 4 0 22 Aug 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 23 22 0 26 Jul 2022
Data Science and Machine Learning in Education G. Benelli Thomas Y. Chen Javier Mauricio Duarte Matthew Feickert Matthew Graham ... K. Terao S. Thais A. Roy J. Vlimant G. Chachamis AI4CE 26 5 0 19 Jul 2022
Neural modal ordinary differential equations: Integrating physics-based modeling with neural ordinary differential equations for modeling high-dimensional monitored structures Zhilu Lai Wei Liu Xudong Jian Kiran Bacsa Limin Sun Eleni Chatzi AI4CE 19 22 0 16 Jul 2022
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 17 1 0 30 Jun 2022
Do Residual Neural Networks discretize Neural Ordinary Differential Equations? Michael E. Sander Pierre Ablin Gabriel Peyré 27 25 0 29 May 2022
Machine Learning for Microcontroller-Class Hardware: A Review Swapnil Sayan Saha S. Sandha Mani B. Srivastava 19 117 0 29 May 2022