Data Learning: Integrating Data Assimilation and Machine Learning

Deep Data Assimilation: Integrating Deep Learning with Data Assimilation

(2021) Rossella Arcucci et al.   Applied Sciences-Basel

Learning earth system models from observations: machine learning or data assimilation?

(2021) A. J. Geer   PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Reduced-Order Quasilinear Model of Ocean Boundary-Layer Turbulence

(2020) Joseph Skitka et al.   JOURNAL OF PHYSICAL OCEANOGRAPHY

Modelling of instantaneous emissions from diesel vehicles with a special focus on NOx: Insights from machine learning techniques

(2020) Clémence M.A. Le Cornec et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

(2020) Julian Mack et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Towards a robust parameterization for conditioning facies models using deep variational autoencoders and ensemble smoother

(2019) Smith W.A. Canchumuni et al.   COMPUTERS & GEOSCIENCES

Leveraging Modern Artificial Intelligence for Remote Sensing and NWP: Benefits and Challenges

(2019) Sid-Ahmed Boukabara et al.   BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY

Deterministic ensemble smoother with multiple data assimilation as an alternative for history-matching seismic data

(2018) Alexandre A. Emerick   COMPUTATIONAL GEOSCIENCES

Non-intrusive reduced order modeling of nonlinear problems using neural networks

(2018) J.S. Hesthaven et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Projection-based model reduction: Formulations for physics-based machine learning

(2018) Renee Swischuk et al.   COMPUTERS & FLUIDS

A reduced order model for turbulent flows in the urban environment using machine learning

(2018) D. Xiao et al.   BUILDING AND ENVIRONMENT

Optimal reduced space for Variational Data Assimilation

(2018) Rossella Arcucci et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Data-driven reduced order modeling for time-dependent problems

(2018) Mengwu Guo et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

On the variational data assimilation problem solving and sensitivity analysis

(2017) Rossella Arcucci et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling

(2017) P. Perdikaris et al.   PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES

Variational data assimilation for parameter estimation: application to a simple morphodynamic model

(2009) Polly J. Smith et al.   OCEAN DYNAMICS

Fast data assimilation using a nonlinear Kalman filter and a model surrogate: An application to the Columbia River estuary

(2008) Sergey Frolov et al.   DYNAMICS OF ATMOSPHERES AND OCEANS