Gemma Anderson

According to our database, Gemma Anderson authored at least 6 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Evaluating probabilistic deep learning methods for uncertainty quantification of temperature downscaling.

Yannic Lops, Gemma J. Anderson, Donald D. Lucas, Indrasis Chakraborty, Daniel Galea

Mach. Learn. Sci. Technol., 2025

2022

Suppressing simulation bias in multi-modal data using transfer learning.

Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Michael K. G. Kruse, Ryan Nora

Mach. Learn. Sci. Technol., 2022

2021

The data-driven future of high-energy-density physics.

Peter W. Hatfield, Jim A. Gaffney, Gemma J. Anderson, Suzanne Ali, Luca Antonelli, Suzan Basegmez du Pree, Jonathan Citrin, Marta Fajardo, Patrick F. Knapp, Brendan Kettle, Bogdan Kustowski, Michael J. MacDonald, Derek Mariscal, Madison E. Martin, Taisuke Nagayama, Charlotte A. J. Palmer, J. Luc Peterson, Steven J. Rose, J. J. Ruby, Carl Shneider, Matt J. V. Streeter, Will Trickey, Ben Williams

Nat., 2021

Transfer learning suppresses simulation bias in predictive models built from sparse, multi-modal data.

Bogdan Kustowski, Jim A. Gaffney, Brian K. Spears, Gemma J. Anderson, Rushil Anirudh, Peer-Timo Bremer, Jayaraman J. Thiagarajan

CoRR, 2021

2020

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

Gemma J. Anderson, Jim A. Gaffney, Brian K. Spears, Peer-Timo Bremer, Rushil Anirudh, Jayaraman J. Thiagarajan

CoRR, 2020

Designing Accurate Emulators for Scientific Processes using Calibration-Driven Deep Models.

Jayaraman J. Thiagarajan, Bindya Venkatesh, Rushil Anirudh, Peer-Timo Bremer, Jim Gaffney, Gemma Anderson, Brian K. Spears

CoRR, 2020