3 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
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…
Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations
Aditya Kashi, Arka Daw, Muralikrishnan Gopalakrishnan Meena +1
Neural operators such as the Fourier Neural Operator (FNO) have been shown to provide resolution-independent deep learning models that can learn mappings between function spaces. F…
Scalable Artificial Intelligence for Science: Perspectives, Methods and Exemplars
Wesley Brewer, Aditya Kashi, Sajal Dash +4
In a post-ChatGPT world, this paper explores the potential of leveraging scalable artificial intelligence for scientific discovery. We propose that scaling up artificial intelligen…