Machine Learning for Prediction with Missing Dynamics

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Machine Learning for Prediction with Missing Dynamics

13 October 2019

Shixiao W. Jiang

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Papers citing "Machine Learning for Prediction with Missing Dynamics"

14 / 14 papers shown

Title
Drivetrain simulation using variational autoencoders Pallavi Sharma Jorge-Humberto Urrea-Quintero Bogdan Bogdan Adrian-Dumitru Ciotec Laura Vasilie Henning Wessels Matteo Skull 457 0 0 01 Jul 2025
A non-intrusive machine learning framework for debiasing long-time coarse resolution climate simulations and quantifying rare events statistics Benedikt Barthel Sorensen A. Charalampopoulos Shixuan Zhang B. Harrop Ruby Leung T. Sapsis AI4Cl 33 10 0 28 Feb 2024
Learning nonlinear integral operators via Recurrent Neural Networks and its application in solving Integro-Differential Equations Hardeep Bassi Yuanran Zhu Senwei Liang Jia Yin Cian C. Reeves Vojtěch Vlček Chao Yang 70 10 0 13 Oct 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 71 10 0 27 Jan 2023
Deep learning delay coordinate dynamics for chaotic attractors from partial observable data Charles D. Young M. Graham 33 16 0 20 Nov 2022
The Mori-Zwanzig formulation of deep learning D. Venturi Xiantao Li 88 1 0 12 Sep 2022
Stochastic Data-Driven Variational Multiscale Reduced Order Models Fei Lu Changhong Mou Honghu Liu T. Iliescu 71 0 0 06 Sep 2022
Discrepancy Modeling Framework: Learning missing physics, modeling systematic residuals, and disambiguating between deterministic and random effects Megan R. Ebers K. Steele J. Nathan Kutz 85 16 0 10 Mar 2022
Learning Stochastic Dynamics with Statistics-Informed Neural Network Yuanran Zhu Yunhao Tang Changho Kim 92 19 0 24 Feb 2022
Generalized statistics: applications to data inverse problems with outlier-resistance João V T de Lima G. Z. dos Santos Lima J. M. de Araújo G. Corso S. D. da Silva 13 7 0 28 Jan 2022
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 87 16 0 01 Oct 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations Georg Gottwald Sebastian Reich AI4CE 94 38 0 08 Aug 2021
Error Bounds of the Invariant Statistics in Machine Learning of Ergodic Itô Diffusions He Zhang J. Harlim Xiantao Li 72 7 0 21 May 2021
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning P. Stinis AI4TS AI4CE 71 11 0 17 May 2019