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DOE CSGF 2011: ____Scale Computing: How Did We Get Here and What's Next
Large-Scale Visual Analysis | Chris Johnson, University of Utah
DOE CSGF 2017: HACC: Fitting the Universe Inside a Supercomputer
DOE CSGF 2022: DOE Office of Science Welcome
DOE CSGF 2019: Reasoning About Biology With Data-Driven Approaches
CalAPA Digging Deeper: Identifying the Equity Gap Analyzing Data
DOE CSGF 2017: Better Science Through Software
DOE CSGF 2017: Welcome - Barbara Helland
DOE CSGF 2011: Robustly finding the needles in a haystack of high-dimensional data
DOE CSGF 2024: Operator Learning for PDEs: Function Space Theory Meets Machine Learning
DOE CSGF 2023: Scientific Machine Learning for Modeling and Simulating Complex Fluids
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Last Updated: October 1, 2026
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Presented at the Argonne Training Program on Extreme- Biology has traditionally been a low-throughput science, where gleaning insights into processes has been slow and expensive. In this video, the Performance Assessment team long with Dr. Delia Estrada and Mr. Daniel Kim from LAUSD discuss best ... "Operator Learning for PDEs: Function Space Theory Meets Machine Learning" presented by Margaret Trautner at the 2024 Presented by Kyle Lennon at the 2023
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