Analyzing Koopman approaches to physics-informed machine learning for
long-term sea-surface temperature forecasting

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Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting

15 September 2020

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Papers citing "Analyzing Koopman approaches to physics-informed machine learning for long-term sea-surface temperature forecasting"

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Title
Deep Koopman operator framework for causal discovery in nonlinear dynamical systems Juan Nathaniel Carla Roesch Jatan Buch Derek DeSantis Adam Rupe Kara Lamb Pierre Gentine CML 62 1 0 20 May 2025
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling Kshitij Tayal Arvind Renganathan Rahul Ghosh X. Jia Vipin Kumar SyDa AI4CE 89 5 0 19 Sep 2023
QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning Di Luo Jiayu Shen Rumen Dangovski Marin Soljacic 79 5 0 02 Nov 2022
Bounded nonlinear forecasts of partially observed geophysical systems with physics-constrained deep learning Said Ouala Steven L. Brunton A. Pascual Bertrand Chapron F. Collard L. Gaultier Ronan Fablet PINN AI4TS AI4CE 71 10 0 11 Feb 2022
CKNet: A Convolutional Neural Network Based on Koopman Operator for Modeling Latent Dynamics from Pixels Yongqian Xiao Xin Xu Yifei Shi 53 9 0 19 Feb 2021
Forecasting Sequential Data using Consistent Koopman Autoencoders Omri Azencot N. Benjamin Erichson Vanessa Lin Michael W. Mahoney AI4TS AI4CE 206 152 0 04 Mar 2020