Bridging observation, theory and numerical simulation of the ocean using
Machine Learning

Bridging observation, theory and numerical simulation of the ocean using Machine Learning

26 April 2021

Maike Sonnewald

Redouane Lguensat

Daniel C. Jones

Venkatramani Balaji

Papers citing "Bridging observation, theory and numerical simulation of the ocean using Machine Learning"

16 / 16 papers shown

Title
Probabilistic Emulation of the Community Radiative Transfer Model Using Machine Learning Lucas Howard Aneesh C. Subramanian Gregory Thompson Benjamin Johnson Thomas Auligne 22 0 0 22 Apr 2025
Hybrid machine learning data assimilation for marine biogeochemistry Ieuan Higgs Ross Bannister Jozef Skákala Alberto Carrassi Stefano Ciavatta AI4Cl AI4CE 14 0 0 07 Apr 2025
A Moonshot for AI Oracles in the Sciences Bryan Kaiser Tailin Wu Maike Sonnewald Colin Thackray Skylar Callis AI4CE 32 0 0 25 Jun 2024
The Importance of Architecture Choice in Deep Learning for Climate Applications Simon Dräger Maike Sonnewald AI4CE 29 1 0 21 Feb 2024
Gradient-free online learning of subgrid-scale dynamics with neural emulators Hugo Frezat Ronan Fablet G. Balarac Julien Le Sommer 16 4 0 30 Oct 2023
OceanBench: The Sea Surface Height Edition J. E. Johnson Q. Febvre Anastasia Gorbunova Sammy Metref M. Ballarotta Julien Le Sommer Ronan Fablet 28 2 0 27 Sep 2023
Multi-fidelity climate model parameterization for better generalization and extrapolation Mohamed Aziz Bhouri Liran Peng Michael S. Pritchard Pierre Gentine AI4CE 16 4 0 19 Sep 2023
AI-GOMS: Large AI-Driven Global Ocean Modeling System Wei Xiong Yanfei Xiang Hao Wu Shuyi Zhou Yuze Sun Muyuan Ma Xiaomeng Huang AI4Cl AI4CE 13 18 0 06 Aug 2023
On the choice of training data for machine learning of geostrophic mesoscale turbulence Fei Er Yan Julian Mak Yan Wang AI4CE 24 2 0 03 Jul 2023
Semi-automatic tuning of coupled climate models with multiple intrinsic timescales: lessons learned from the Lorenz96 model Redouane Lguensat Julie Deshayes Homer Durand Venkatramani Balaji 29 4 0 11 Aug 2022
Dimensionally Consistent Learning with Buckingham Pi Joseph Bakarji Jared L. Callaham Steven L. Brunton N. Kutz 23 38 0 09 Feb 2022
Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation Julian Mack Rossella Arcucci Miguel Molina-Solana Yi-Ke Guo 3DPC 48 34 0 06 Jan 2021
Model error covariance estimation in particle and ensemble Kalman filters using an online expectation-maximization algorithm T. Cocucci M. Pulido M. Lucini P. Tandeo 28 11 0 04 Mar 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,233 0 24 Jun 2017
A Random Forest Guided Tour Gérard Biau Erwan Scornet AI4TS 139 2,711 0 18 Nov 2015
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 201 7,884 0 13 Jun 2015