2 papers
cs.LG2025
Intelligent Sampling of Extreme-Scale Turbulence Datasets for Accurate and Efficient Spatiotemporal Model Training
Wesley Brewer, Murali Meena Gopalakrishnan, Matthias Maiterth +12
With the end of Moore's law and Dennard scaling, efficient training increasingly requires rethinking data volume. Can we train better models with significantly less data via intell…
physics.flu-dyn2024
Routes to stratified turbulence and temporal intermittency revealed by a cluster-based network model of experimental data
Adrien Lefauve, Yui Hin Marvil Cheung, Xianyang Jiang +1
Modelling fluid turbulence using a `skeleton' of coherent structures has traditionally progressed by focusing on a few canonical laboratory experiments such as pipe flow and Taylor…