Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems

4 January 2018

Papers citing "Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems"

50 / 133 papers shown

Title
A Neural Network Ensemble Approach to System Identification Elisa Negrini G. Citti L. Capogna 22 2 0 15 Oct 2021
Learning Dynamics from Noisy Measurements using Deep Learning with a Runge-Kutta Constraint P. Goyal P. Benner 43 9 0 23 Sep 2021
Recurrent Neural Networks for Partially Observed Dynamical Systems Uttam Bhat S. Munch PINN AI4CE 19 8 0 21 Sep 2021
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling Franck Djeumou Cyrus Neary Eric Goubault S. Putot Ufuk Topcu PINN AI4CE 47 69 0 14 Sep 2021
Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics Oliver K. Ernst T. Bartol T. Sejnowski E. Mjolsness 14 0 0 10 Sep 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 62 37 0 09 Sep 2021
GFINNs: GENERIC Formalism Informed Neural Networks for Deterministic and Stochastic Dynamical Systems Zhen Zhang Yeonjong Shin George Karniadakis AI4CE 31 52 0 31 Aug 2021
Data-Driven Reduced-Order Modeling of Spatiotemporal Chaos with Neural Ordinary Differential Equations Alec J. Linot M. Graham 22 48 0 31 Aug 2021
A Framework for Machine Learning of Model Error in Dynamical Systems Matthew E. Levine Andrew M. Stuart 27 67 0 14 Jul 2021
Deep Neural Network Modeling of Unknown Partial Differential Equations in Nodal Space Zhen Chen V. Churchill Kailiang Wu D. Xiu AI4CE 14 47 0 07 Jun 2021
Learning particle swarming models from data with Gaussian processes Jinchao Feng Charles Kulick Yunxiang Ren Sui Tang 31 5 0 04 Jun 2021
MAGI-X: Manifold-Constrained Gaussian Process Inference for Unknown System Dynamics Chaofan Huang Simin Ma Shihao Yang 30 0 0 27 May 2021
Learning Runge-Kutta Integration Schemes for ODE Simulation and Identification Said Ouala L. Debreu A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet 26 4 0 11 May 2021
Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach P. Goyal P. Benner 33 48 0 11 May 2021
Granger Causality: A Review and Recent Advances Ali Shojaie E. Fox CML AI4TS 37 260 0 05 May 2021
Dominant motion identification of multi-particle system using deep learning from video Yayati Jadhav Amir Barati Farimani 29 4 0 26 Apr 2021
A Temporal Kernel Approach for Deep Learning with Continuous-time Information Da Xu Chuanwei Ruan Evren Körpeoglu Sushant Kumar Kannan Achan SyDa AI4TS 22 4 0 28 Mar 2021
The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation Q. Du Yiqi Gu Haizhao Yang Chao Zhou 26 20 0 21 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 655 0 20 Mar 2021
Meta-Solver for Neural Ordinary Differential Equations Julia Gusak A. Katrutsa Talgat Daulbaev A. Cichocki Ivan Oseledets 16 2 0 15 Mar 2021
Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps Ren-Chuen Chen Molei Tao 32 51 0 09 Mar 2021
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data Mohamed Aziz Bhouri P. Perdikaris 31 20 0 04 Mar 2021
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran PINN AI4CE 29 76 0 25 Feb 2021
Learning elliptic partial differential equations with randomized linear algebra Nicolas Boullé Alex Townsend 19 41 0 31 Jan 2021
Learning Interaction Kernels for Agent Systems on Riemannian Manifolds Mauro Maggioni Jason D Miller H. Qui Ming Zhong 19 8 0 30 Jan 2021
STENCIL-NET: Data-driven solution-adaptive discretization of partial differential equations S. Maddu D. Sturm B. Cheeseman Christian L. Müller I. Sbalzarini 32 8 0 15 Jan 2021
Accuracy and Architecture Studies of Residual Neural Network solving Ordinary Differential Equations Changxin Qiu Aaron Bendickson Joshua Kalyanapu Jue Yan 10 1 0 10 Jan 2021
Constrained Block Nonlinear Neural Dynamical Models Elliott Skomski Soumya Vasisht Colby Wight Aaron Tuor Ján Drgoňa D. Vrabie AI4CE 32 15 0 06 Jan 2021
Reduced Order Modeling using Shallow ReLU Networks with Grassmann Layers K. Bollinger Hayden Schaeffer 9 2 0 17 Dec 2020
A Data Driven Method for Computing Quasipotentials Bo Lin Qianxiao Li W. Ren 16 13 0 13 Dec 2020
Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks Pengzhan Jin Zhen Zhang Ioannis G. Kevrekidis George Karniadakis 38 50 0 05 Dec 2020
Nested Mixture of Experts: Cooperative and Competitive Learning of Hybrid Dynamical System Junhyeok Ahn Luis Sentis 34 3 0 20 Nov 2020
Data-driven Identification of 2D Partial Differential Equations using extracted physical features Kazem Meidani A. Farimani 21 17 0 20 Oct 2020
Operator Inference and Physics-Informed Learning of Low-Dimensional Models for Incompressible Flows P. Benner P. Goyal Jan Heiland I. P. Duff AI4CE 9 26 0 13 Oct 2020
Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems Jason D Miller Sui Tang Ming Zhong Mauro Maggioni 26 18 0 08 Oct 2020
Knowledge-Based Learning of Nonlinear Dynamics and Chaos Tom Z. Jiahao M. Hsieh Eric Forgoston 29 31 0 07 Oct 2020
Discovery of Governing Equations with Recursive Deep Neural Networks Jia Zhao Jarrod Mau PINN 32 6 0 24 Sep 2020
OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle Haijun Yu Xinyuan Tian Weinan E Qianxiao Li AI4CE 30 42 0 06 Sep 2020
Variational Deep Learning for the Identification and Reconstruction of Chaotic and Stochastic Dynamical Systems from Noisy and Partial Observations Duong Nguyen Said Ouala Lucas Drumetz Ronan Fablet 15 13 0 04 Sep 2020
Bridging the Gap: Machine Learning to Resolve Improperly Modeled Dynamics Maan Qraitem D. Kularatne Eric Forgoston M. A. Hsieh AI4CE 31 10 0 23 Aug 2020
Hierarchical Deep Learning of Multiscale Differential Equation Time-Steppers Yuying Liu N. Kutz Steven L. Brunton AI4TS 12 75 0 22 Aug 2020
Hypersolvers: Toward Fast Continuous-Depth Models Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park BDL AI4CE 22 46 0 19 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 20 219 0 09 Jul 2020
Phase space learning with neural networks Jaime Lopez Garcia Ángel Rivero Jiménez AI4CE 9 0 0 22 Jun 2020
Neural Vortex Method: from Finite Lagrangian Particles to Infinite Dimensional Eulerian Dynamics S. Xiong Xingzhe He Yunjin Tong Yitong Deng Bo Zhu 21 11 0 07 Jun 2020
Data-driven learning of non-autonomous systems Tong Qin Zhen Chen J. Jakeman D. Xiu 10 19 0 02 Jun 2020
Revealing hidden dynamics from time-series data by ODENet Pipi Hu Wuyue Yang Yi Zhu L. Hong AI4TS 24 35 0 11 May 2020
Active Training of Physics-Informed Neural Networks to Aggregate and Interpolate Parametric Solutions to the Navier-Stokes Equations Christopher J. Arthurs A. King PINN 43 51 0 02 May 2020
Bayesian differential programming for robust systems identification under uncertainty Yibo Yang Mohamed Aziz Bhouri P. Perdikaris OOD 33 32 0 15 Apr 2020
Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators J. Kadupitiya Geoffrey C. Fox V. Jadhao AI4CE 17 20 0 12 Apr 2020