Hamiltonian Generative Networks

30 September 2019

Peter Toth

Danilo Jimenez Rezende

Papers citing "Hamiltonian Generative Networks"

46 / 46 papers shown

Title
Hamiltonian Normalizing Flows as kinetic PDE solvers: application to the 1D Vlasov-Poisson Equations Vincent Souveton Sébastien Terrana 41 0 0 07 May 2025
Unsupervised Representation Learning from Sparse Transformation Analysis Yue Song Thomas Anderson Keller Yisong Yue Pietro Perona Max Welling DRL 29 0 0 07 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 38 0 0 02 Oct 2024
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control T. Duong Abdullah Altawaitan Jason Stanley Nikolay A. Atanasov 28 10 0 17 Jan 2024
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 31 8 0 29 Dec 2023
Hamiltonian GAN Christine Allen-Blanchette GAN AI4CE 29 1 0 22 Aug 2023
Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models Sarvin Moradi N. Jaensson Roland Tóth Maarten Schoukens PINN 30 3 0 02 May 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity Vincent Souveton Arnaud Guillin J. Jasche G. Lavaux Manon Michel 20 3 0 03 Feb 2023
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
Neural Langevin Dynamics: towards interpretable Neural Stochastic Differential Equations Simon Koop M. Peletier J. Portegies Vlado Menkovski DiffM 27 1 0 17 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
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 31 84 0 18 Oct 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
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
Lagrangian Density Space-Time Deep Neural Network Topology B. Bishnoi PINN 22 1 0 30 Jun 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 36 55 0 31 Mar 2022
Learning Neural Hamiltonian Dynamics: A Methodological Overview Zhijie Chen Mingquan Feng Junchi Yan H. Zha AI4CE 19 15 0 28 Feb 2022
Reconstruction of observed mechanical motions with Artificial Intelligence tools Antal Jakovác M. T. Kurbucz Péter Pósfay 9 8 0 23 Feb 2022
Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately A. Sosanya S. Greydanus PINN AI4CE 38 27 0 25 Jan 2022
Learning Large-Time-Step Molecular Dynamics with Graph Neural Networks Tian Zheng Weihao Gao Chong-Jun Wang AI4CE 28 3 0 30 Nov 2021
Characteristic Neural Ordinary Differential Equations Xingzi Xu Ali Hasan Khalil Elkhalil Jie Ding Vahid Tarokh BDL 23 3 0 25 Nov 2021
Physics-enhanced Neural Networks in the Small Data Regime Jonas Eichelsdörfer Sebastian Kaltenbach P. Koutsourelakis AI4CE PINN 12 5 0 19 Nov 2021
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision I. Higgins Peter Wirnsberger Andrew Jaegle Aleksandar Botev 37 7 0 10 Nov 2021
Which priors matter? Benchmarking models for learning latent dynamics Aleksandar Botev Andrew Jaegle Peter Wirnsberger Daniel Hennes I. Higgins AI4CE 27 28 0 09 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 28 93 0 02 Nov 2021
Kinematically consistent recurrent neural networks for learning inverse problems in wave propagation Wrik Mallik R. Jaiman J. Jelovica AI4CE 25 3 0 08 Oct 2021
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling Kookjin Lee Nathaniel Trask P. Stinis 32 24 0 11 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 25 43 0 16 Jul 2021
Machine learning structure preserving brackets for forecasting irreversible processes Kookjin Lee Nathaniel Trask P. Stinis AI4CE 36 42 0 23 Jun 2021
Symplectic Learning for Hamiltonian Neural Networks M. David Florian Méhats 13 34 0 22 Jun 2021
Learning Deep Energy Shaping Policies for Stability-Guaranteed Manipulation S. A. Khader Hang Yin Pietro Falco Danica Kragic 6 12 0 30 Mar 2021
The Hintons in your Neural Network: a Quantum Field Theory View of Deep Learning Roberto Bondesan Max Welling 42 7 0 08 Mar 2021
Adaptable Hamiltonian neural networks Chen-Di Han Bryan Glaz Mulugeta Haile Y. Lai AI4TS 22 25 0 25 Feb 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling Naoya Takeishi Alexandros Kalousis DRL AI4CE 24 54 0 25 Feb 2021
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
Learning Thermodynamically Stable and Galilean Invariant Partial Differential Equations for Non-equilibrium Flows Juntao Huang Zhiting Ma Y. Zhou W. Yong AI4CE 27 16 0 28 Sep 2020
TorchDyn: A Neural Differential Equations Library Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 16 24 0 20 Sep 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 33 25 0 23 Jun 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Stochastic Normalizing Flows Hao Wu Jonas Köhler Frank Noé 54 176 0 16 Feb 2020
SympNets: Intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems Pengzhan Jin Zhen Zhang Aiqing Zhu Yifa Tang George Karniadakis 16 21 0 11 Jan 2020
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 24 30 0 22 Oct 2019