A Framework for Machine Learning of Model Error in Dynamical Systems

14 July 2021

Papers citing "A Framework for Machine Learning of Model Error in Dynamical Systems"

36 / 36 papers shown

Title
How more data can hurt: Instability and regularization in next-generation reservoir computing Yuanzhao Zhang Edmilson Roque dos Santos Sean P. Cornelius 77 2 0 28 Jan 2025
Structural Constraints for Physics-augmented Learning Simon Kuang Xinfan Lin PINN 26 0 0 07 Oct 2024
Zero-shot forecasting of chaotic systems Yuanzhao Zhang William Gilpin AI4TS 37 4 0 24 Sep 2024
Beyond Closure Models: Learning Chaotic-Systems via Physics-Informed Neural Operators Chuwei Wang Julius Berner Zongyi Li Di Zhou Jiayun Wang Jane Bae Anima Anandkumar AI4CE 28 1 0 09 Aug 2024
On the choice of the non-trainable internal weights in random feature maps Pinak Mandal Georg Gottwald Nicholas Cranch TPM 33 1 0 07 Aug 2024
Learning Optimal Filters Using Variational Inference Enoch Luk Eviatar Bach Ricardo Baptista Andrew Stuart 24 6 0 26 Jun 2024
Online model error correction with neural networks: application to the Integrated Forecasting System A. Farchi M. Chrust Marc Bocquet Massimo Bonavita 16 0 0 06 Mar 2024
Hybrid $^2$ Neural ODE Causal Modeling and an Application to Glycemic Response Bob Junyi Zou Matthew E. Levine D. Zaharieva Ramesh Johari Emily Fox 33 4 0 27 Feb 2024
Learning Semilinear Neural Operators : A Unified Recursive Framework For Prediction And Data Assimilation Ashutosh Singh R. Borsoi Deniz Erdogmus Tales Imbiriba 47 0 0 24 Feb 2024
Pathspace Kalman Filters with Dynamic Process Uncertainty for Analyzing Time-course Data Chaitra Agrahar William Poole Simone Bianco Hana El-Samad 11 0 0 07 Feb 2024
Learning About Structural Errors in Models of Complex Dynamical Systems Jin-Long Wu Matthew E. Levine Tapio Schneider Andrew M. Stuart AI4CE 10 17 0 29 Dec 2023
Hybrid Modeling Design Patterns Maja Rudolph Stefan Kurz Barbara Rakitsch AI4CE 18 7 0 29 Dec 2023
Interpretable Mechanistic Representations for Meal-level Glycemic Control in the Wild Ke Alexander Wang Emily B. Fox DRL 14 0 0 06 Dec 2023
Interpretable structural model error discovery from sparse assimilation increments using spectral bias-reduced neural networks: A quasi-geostrophic turbulence test case R. Mojgani A. Chattopadhyay P. Hassanzadeh 27 7 0 22 Sep 2023
Reservoir Computing with Error Correction: Long-term Behaviors of Stochastic Dynamical Systems Cheng Fang Yubin Lu Ting Gao Jinqiao Duan 25 4 0 01 May 2023
Learning Absorption Rates in Glucose-Insulin Dynamics from Meal Covariates Ke Alexander Wang Matthew E. Levine Jiaxin Shi E. Fox 19 3 0 27 Apr 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 24 121 0 18 Mar 2023
Reduced-Order Autodifferentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 28 8 0 27 Jan 2023
Online model error correction with neural networks in the incremental 4D-Var framework A. Farchi M. Chrust Marc Bocquet P. Laloyaux Massimo Bonavita 39 16 0 25 Oct 2022
Catch-22s of reservoir computing Yuanzhao Zhang Sean P. Cornelius 11 10 0 18 Oct 2022
Stochastic Data-Driven Variational Multiscale Reduced Order Models Fei Lu Changhong Mou Honghu Liu T. Iliescu 13 0 0 06 Sep 2022
Quantum Mechanics for Closure of Dynamical Systems D. Freeman D. Giannakis J. Slawinska 21 4 0 05 Aug 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 8 84 0 13 Apr 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 20 15 0 10 Mar 2022
Robust Hybrid Learning With Expert Augmentation Antoine Wehenkel Jens Behrmann Hsiang Hsu Guillermo Sapiro Gilles Louppe and J. Jacobsen 21 8 0 08 Feb 2022
Efficient Multifidelity Likelihood-Free Bayesian Inference with Adaptive Computational Resource Allocation Thomas P. Prescott D. Warne R. Baker 12 6 0 22 Dec 2021
Physics-enhanced deep surrogates for partial differential equations R. Pestourie Youssef Mroueh Chris Rackauckas Payel Das Steven G. Johnson PINN AI4CE 14 15 0 10 Nov 2021
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani A. Chattopadhyay P. Hassanzadeh 19 15 0 01 Oct 2021
Combining machine learning and data assimilation to forecast dynamical systems from noisy partial observations Georg Gottwald Sebastian Reich AI4CE 31 37 0 08 Aug 2021
Auto-differentiable Ensemble Kalman Filters Yuming Chen D. Sanz-Alonso Rebecca Willett 32 33 0 16 Jul 2021
Learning Dissipative Dynamics in Chaotic Systems Zong-Yi Li Miguel Liu-Schiaffini Nikola B. Kovachki Burigede Liu Kamyar Azizzadenesheli K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 16 25 0 13 Jun 2021
Learning to Control an Unstable System with One Minute of Data: Leveraging Gaussian Process Differentiation in Predictive Control I. D. Rodriguez Ugo Rosolia Aaron D. Ames Yisong Yue 18 2 0 08 Mar 2021
Fourier Series-Based Approximation of Time-Varying Parameters in Ordinary Differential Equations Anna Fitzpatrick Molly Folino Andrea Arnold 6 0 0 21 Jan 2021
Fourier Neural Operator for Parametric Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar AI4CE 203 2,272 0 18 Oct 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems J. Willard X. Jia Shaoming Xu M. Steinbach Vipin Kumar AI4CE 80 385 0 10 Mar 2020
Combining Machine Learning with Knowledge-Based Modeling for Scalable Forecasting and Subgrid-Scale Closure of Large, Complex, Spatiotemporal Systems Alexander Wikner Jaideep Pathak Brian Hunt M. Girvan T. Arcomano I. Szunyogh Andrew Pomerance Edward Ott AI4CE 62 70 0 10 Feb 2020