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
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
Learning Contact Dynamics using Physically Structured Neural Networks Andreas Hochlehnert Alexander Terenin Steindór Sæmundsson M. Deisenroth 14 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
A Differential Geometry Perspective on Orthogonal Recurrent Models Omri Azencot N. Benjamin Erichson M. Ben-Chen Michael W. Mahoney AI4CE 8 5 0 18 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
Noisy Recurrent Neural Networks S. H. Lim N. Benjamin Erichson Liam Hodgkinson Michael W. Mahoney 12 52 0 09 Feb 2021
Continuous-Time Model-Based Reinforcement Learning Çağatay Yıldız Markus Heinonen Harri Lähdesmäki OffRL 13 52 0 09 Feb 2021
Physics-aware, probabilistic model order reduction with guaranteed stability Sebastian Kaltenbach P. Koutsourelakis DiffM AI4CE 8 15 0 14 Jan 2021
Optimal Energy Shaping via Neural Approximators Stefano Massaroli Michael Poli Federico Califano Jinkyoo Park Atsushi Yamashita Hajime Asama 16 12 0 14 Jan 2021
Structured learning of rigid-body dynamics: A survey and unified view from a robotics perspective A. R. Geist Sebastian Trimpe AI4CE 6 17 0 11 Dec 2020
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 22 47 0 03 Dec 2020
Learning Principle of Least Action with Reinforcement Learning Zehao Jin J. Lin Siao-Fong Li 11 3 0 24 Nov 2020
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System Junhyeok Ahn Luis Sentis 26 3 0 20 Nov 2020
Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics Ján Drgoňa Aaron Tuor V. Chandan D. Vrabie AI4CE 19 115 0 11 Nov 2020
NeuralSim: Augmenting Differentiable Simulators with Neural Networks Eric Heiden David Millard Erwin Coumans Yizhou Sheng Gaurav Sukhatme 19 136 0 09 Nov 2020
Leveraging Forward Model Prediction Error for Learning Control Sarah Bechtle Bilal Hammoud Akshara Rai Franziska Meier Ludovic Righetti 14 3 0 07 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
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 26 126 0 26 Oct 2020
LagNetViP: A Lagrangian Neural Network for Video Prediction Christine Allen-Blanchette Sushant Veer Anirudha Majumdar Naomi Ehrich Leonard 33 30 0 24 Oct 2020
Nonseparable Symplectic Neural Networks S. Xiong Yunjin Tong Xingzhe He Shuqi Yang Cheng Yang Bo Zhu 21 32 0 23 Oct 2020
A Differentiable Newton Euler Algorithm for Multi-body Model Learning M. Lutter Johannes Silberbauer Joe Watson Jan Peters 8 11 0 19 Oct 2020
POMDPs in Continuous Time and Discrete Spaces Bastian Alt M. Schultheis Heinz Koeppl 11 9 0 02 Oct 2020
The Role of Isomorphism Classes in Multi-Relational Datasets Vijja Wichitwechkarn Ben Day Cristian Bodnar Matthew Wales Pietro Lió 43 0 0 30 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
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
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 23 159 0 16 Jul 2020
Augmenting Differentiable Simulators with Neural Networks to Close the Sim2Real Gap Eric Heiden David Millard Erwin Coumans Gaurav Sukhatme 19 21 0 12 Jul 2020
Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control Yaofeng Desmond Zhong Naomi Ehrich Leonard DRL AI4CE 19 43 0 03 Jul 2020
Learning Potentials of Quantum Systems using Deep Neural Networks Arijit Sehanobish H. Corzo Onur Kara David van Dijk 6 12 0 23 Jun 2020
Learning Physical Constraints with Neural Projections Shuqi Yang Xingzhe He Bo Zhu 3DV AI4CE 33 25 0 23 Jun 2020
Scalable Identification of Partially Observed Systems with Certainty-Equivalent EM Kunal Menda J. Becdelievre Jayesh K. Gupta I. Kroo Mykel J. Kochenderfer Zachary Manchester 6 6 0 20 Jun 2020
Learning Dynamics Models with Stable Invariant Sets Naoya Takeishi Yoshinobu Kawahara 10 17 0 16 Jun 2020
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning Sungyong Seo Chuizheng Meng Sirisha Rambhatla Yan Liu AI4CE 13 11 0 15 Jun 2020
On Second Order Behaviour in Augmented Neural ODEs Alexander Norcliffe Cristian Bodnar Ben Day Nikola Simidjievski Pietro Lió 28 90 0 12 Jun 2020
Continuous-time system identification with neural networks: Model structures and fitting criteria Marco Forgione Dario Piga 6 65 0 03 Jun 2020
Modeling System Dynamics with Physics-Informed Neural Networks Based on Lagrangian Mechanics Manuel A. Roehrl Thomas Runkler Veronika Brandtstetter Michel Tokic Stefan Obermayer PINN 19 77 0 29 May 2020
Learning Constrained Dynamics with Gauss Principle adhering Gaussian Processes A. R. Geist Sebastian Trimpe 12 20 0 23 Apr 2020
Structured Mechanical Models for Robot Learning and Control Jayesh K. Gupta Kunal Menda Zachary Manchester Mykel J. Kochenderfer DRL 18 34 0 21 Apr 2020
In-Hand Object-Dynamics Inference using Tactile Fingertips Balakumar Sundaralingam Tucker Hermans 6 30 0 30 Mar 2020
Learning to Fly via Deep Model-Based Reinforcement Learning Philip Becker-Ehmck Maximilian Karl Jan Peters Patrick van der Smagt SSL 32 37 0 19 Mar 2020
SAPIEN: A SimulAted Part-based Interactive ENvironment Fanbo Xiang Yuzhe Qin Kaichun Mo Yikuan Xia Hao Zhu ... He-Nan Wang Li Yi Angel X. Chang Leonidas J. Guibas Hao Su 218 487 0 19 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 130 424 0 10 Mar 2020
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 13 141 0 04 Mar 2020
Dissipative SymODEN: Encoding Hamiltonian Dynamics with Dissipation and Control into Deep Learning Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN AI4CE 34 78 0 20 Feb 2020
Linearly Constrained Neural Networks J. Hendriks Carl Jidling A. Wills Thomas B. Schon 16 33 0 05 Feb 2020
Encoding Physical Constraints in Differentiable Newton-Euler Algorithm Giovanni Sutanto Austin S. Wang Yixin Lin Mustafa Mukadam Gaurav Sukhatme Akshara Rai Franziska Meier 88 54 0 24 Jan 2020
Automatic Differentiation and Continuous Sensitivity Analysis of Rigid Body Dynamics David Millard Eric Heiden Shubham Agrawal Gaurav Sukhatme AI4CE 19 13 0 22 Jan 2020
Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework Wanxin Jin Zhaoran Wang Zhuoran Yang Shaoshuai Mou 24 77 0 30 Dec 2019
Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe H. Qin 24 0 0 22 Oct 2019