Search Results for author: Gemma J. Anderson

Found 3 papers, 0 papers with code

Suppressing simulation bias using multi-modal data

no code implementations19 Apr 2021 Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Michael K. G. Kruse, Ryan C. Nora

The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

Transfer Learning

Improving seasonal forecast using probabilistic deep learning

no code implementations27 Oct 2020 Baoxiang Pan, Gemma J. Anderson, Andre Goncalves, Donald D. Lucas, CEline J. W. Bonfils, Jiwoo Lee

We apply this probabilistic forecast methodology to quantify the impacts of initialization errors and model formulation deficiencies in a dynamical seasonal forecasting system.

Benchmarking Probabilistic Deep Learning

Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations

no code implementations26 Oct 2020 Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan

Large-scale numerical simulations are used across many scientific disciplines to facilitate experimental development and provide insights into underlying physical processes, but they come with a significant computational cost.

Variational Inference

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