Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks

5 December 2020

Pengzhan Jin

Zhen Zhang

Ioannis G. Kevrekidis

George Karniadakis

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Papers citing "Learning Poisson systems and trajectories of autonomous systems via Poisson neural networks"

21 / 21 papers shown

Title
Approximation capabilities of measure-preserving neural networks Aiqing Zhu Pengzhan Jin Yifa Tang 70 8 0 21 Jun 2021
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints Marc Finzi Ke Alexander Wang A. Wilson AI4CE 88 130 0 26 Oct 2020
Nonseparable Symplectic Neural Networks S. Xiong Yunjin Tong Xingzhe He Shuqi Yang Cheng Yang Bo Zhu 104 34 0 23 Oct 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 76 31 0 10 Jun 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 157 79 0 11 Mar 2020
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 180 438 0 10 Mar 2020
Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamics Pantelis R. Vlachas Jaideep Pathak Brian R. Hunt T. Sapsis M. Girvan Edward Ott Petros Koumoutsakos AI4TS 92 399 0 09 Oct 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 79 218 0 30 Sep 2019
Equivariant Hamiltonian Flows Danilo Jimenez Rezende S. Racanière I. Higgins Peter Toth 80 64 0 30 Sep 2019
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 209 225 0 29 Sep 2019
Hamiltonian Graph Networks with ODE Integrators Alvaro Sanchez-Gonzalez V. Bapst Kyle Cranmer Peter W. Battaglia AI4CE 104 179 0 27 Sep 2019
Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control Yaofeng Desmond Zhong Biswadip Dey Amit Chakraborty PINN 112 271 0 26 Sep 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 139 899 0 04 Jun 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 472 5,176 0 19 Jun 2018
Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems M. Raissi P. Perdikaris George Karniadakis PINN 156 266 0 04 Jan 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 217 505 0 27 Oct 2017
Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang Lili Meng E. Haber Lars Ruthotto David Begert E. Holtham AI4CE 97 264 0 12 Sep 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 159 735 0 09 May 2017
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 277 3,723 0 26 May 2016
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.2K 150,501 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 146 2,269 0 30 Oct 2014