455 citations · 711 across the 25 of their papers we have counts for
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SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning
Pu Ren, N. Benjamin Erichson, Junyi Guo +4
Super-resolution (SR) techniques aim to enhance data resolution, enabling the retrieval of finer details, and improving the overall quality and fidelity of the data representation.…
Towards Stability of Autoregressive Neural Operators
Michael McCabe, Peter Harrington, Shashank Subramanian +1
Neural operators have proven to be a promising approach for modeling spatiotemporal systems in the physical sciences. However, training these models for large systems can be quite…
Towards Foundation Models for Scientific Machine Learning: Characterizing Scaling and Transfer Behavior
Shashank Subramanian, Peter Harrington, Kurt Keutzer +4
Pre-trained machine learning (ML) models have shown great performance for a wide range of applications, in particular in natural language processing (NLP) and computer vision (CV).…