Bounded nonlinear forecasts of partially observed geophysical systems
with physics-constrained deep learning

Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning

11 February 2022

Steven L. Brunton

Bertrand Chapron

Papers citing "Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning"

8 / 8 papers shown

Title
Dynamical system prediction from sparse observations using deep neural networks with Voronoi tessellation and physics constraint Hanyang Wang Hao Zhou Sibo Cheng AI4CE 35 5 0 31 Aug 2024
Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series Akifumi Okuno Y. Morishita Yoh-ichi Mototake AI4TS 16 0 0 28 Jun 2023
Machine learning with data assimilation and uncertainty quantification for dynamical systems: a review Sibo Cheng César Quilodrán-Casas Said Ouala A. Farchi Che Liu ... Weiping Ding Yike Guo A. Carrassi Marc Bocquet Rossella Arcucci AI4CE 32 124 0 18 Mar 2023
Benchmarking sparse system identification with low-dimensional chaos A. Kaptanoglu Lanyue Zhang Zachary G. Nicolaou Urban Fasel Steven L. Brunton 50 20 0 04 Feb 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable data Charles D. Young M. Graham 11 16 0 20 Nov 2022
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 186 763 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 135 510 0 11 Mar 2020
Episodic Learning with Control Lyapunov Functions for Uncertain Robotic Systems Andrew J. Taylor Victor D. Dorobantu Hoang Minh Le Yisong Yue Aaron D. Ames 117 78 0 04 Mar 2019