no code implementations • 11 Jan 2023 • Derek DeSantis, Ayan Biswas, Earl Lawrence, Phillip Wolfram
In this study, we propose a new method for combining in situ buoy measurements with Earth system models (ESMs) to improve the accuracy of temperature predictions in the ocean.
no code implementations • 24 Aug 2022 • Steven Stetzler, Michael Grosskopf, Earl Lawrence
This work examines the accuracy-runtime trade-off of several approximate Gaussian process models -- the sparse variational GP, stochastic variational GP, and deep kernel learned GP -- when emulating the predictions of density functional theory (DFT) models.
no code implementations • 31 Aug 2020 • Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram, Earl Lawrence, Nathan Urban
With the increasing computational power of current supercomputers, the size of data produced by scientific simulations is rapidly growing.
1 code implementation • 1 May 2020 • Matthias Katzfuss, Joseph Guinness, Earl Lawrence
Many scientific phenomena are studied using computer experiments consisting of multiple runs of a computer model while varying the input settings.
1 code implementation • 11 Aug 2015 • Katrin Heitmann, Derek Bingham, Earl Lawrence, Steven Bergner, Salman Habib, David Higdon, Adrian Pope, Rahul Biswas, Hal Finkel, Nicholas Frontiere, Suman Bhattacharya
The new sampling method allows us to build precision emulators from just 26 cosmological models and to increase the emulator accuracy by adding new sets of simulations in a prescribed way.
Cosmology and Nongalactic Astrophysics