CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints

18 February 2025

Papers citing "CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints"

5 / 5 papers shown

Title
ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responsesnpj Climate and Atmospheric Science (npj Clim. Atmos. Sci.), 2024 Oliver Watt-Meyer Brian Henn Jeremy McGibbon Spencer K. Clark Anna Kwa W. Perkins E. Wu L. Harris Christopher S. Bretherton AI4Cl 316 41 0 18 Nov 2024
Neural General Circulation Models for Weather and Climate Dmitrii Kochkov J. Yuval I. Langmore Peter C. Norgaard Jamie A. Smith ... Peter W. Battaglia Alvaro Sanchez-Gonzalez Matthew Willson Michael P. Brenner Stephan Hoyer AI4Cl AI4CE 305 275 0 13 Nov 2023
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networksJournal of machine learning research (JMLR), 2021 Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 478 833 0 31 Jan 2021
Achieving Conservation of Energy in Neural Network Emulators for Climate Modeling Tom Beucler S. Rasp Michael S. Pritchard Pierre Gentine 93 87 0 15 Jun 2019
Deep learning to represent sub-grid processes in climate models S. Rasp Michael S. Pritchard Pierre Gentine AI4Cl AI4CE 232 783 0 12 Jun 2018