Non-Stationary Gaussian Processes at High-Performance Computing Scales for the Space Domain

Executive Summary

We will develop novel machine-learning algorithms with principled uncertainty quantification for large, complex scientific data that support high-fidelity modeling at heretofore intractable scales. This capability will enable scientific and security advancements in the space domain, empowering data-intensive missions with scalable, predictive tools featuring statistical interpretability and uncertainty quantification.

Publications, Presentations, and Patents

Muyskens, Amanda L., Imène R. Goumiri, Benjamin W. Priest, Michael D. Schneider, Robert E. Armstrong, Jason Bernstein, and Ryan Dana. 2022. “Star-Galaxy Image Separation with Computationally Efficient Gaussian Process Classification.” The Astronomical Journal 163, (04 2022): 148. https://doi.org/10.3847/1538-3881/ac4e93.

Goumiri, Imène. “Light Curve Completion and Forecasting Using Fast and Scalable Gaussian Processes (MuyGPs).” Presentation at the Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, Maui, HI. September 27-30, 2022.

Muyskens, Amanda. “MuyGPs: Scalable Gaussian Process Model Estimation with Uncertainty Quantification.” Presentation in the American Statical Association’s (ASA) Section on Defense and National Security (SDNS) Webinar Series, Livermore, CA. September 21, 2022.

Muyskens, Amanda. “MuyGPs: Scalable Gaussian Process Model Estimation with Uncertainty Quantification.” Presentation at the Quality and Productivity Research Conference (QPRC), San Francisco, CA. June 13-16, 2022.

Muyskens, Amanda. “MuyGPs: Scalable Gaussian Process Model Estimation with Uncertainty Quantification.” Presentation at the Space Systems Command (SSC)'s SDA Data Science Working Group (DSWG) meeting held at Lawrence Livermore National Laboratory (LLNL), Livermore, CA. June 7-8, 2022.

Muyskens, Amanda. “MuyGPs: Scalable Gaussian Process Model Estimation with Uncertainty Quantification.” Presentation in the DMS Statistics and Data Science Seminar Series at Auburn University, Auburn, AL. March 17, 2022.