Resources (1-2 of 2)

1. Accelerating Subglacial Bed Topography Prediction in Greenland: A Performance Evaluation of Spark-Optimized Machine Learning Models

   24 Oct 2024 | Contributor(s):: Mostafa Cham, Tartela Tabassum, Ehsan Shakeri, Jianwu Wang

   Accurate estimation of subglacial bed topography is crucial for understanding ice sheet dynamics and their responses to climate change. In this study, we employ machine learning models, enhanced with Spark parallelization, to predict subglacial bed elevation using surface attributes such as ice...

2. Regression on Ice: Function approximation for the mathematically-inclined glaciologist

   17 Sep 2023 | Contributor(s):: Noah J Bergam

   Modern satellite-based analysis of the ice sheets presents a profound statistical-geometric problem: how do we make sense of scattered, noisy measurements of vast, steadily evolving surfaces like the Greenland and Antarctic ice sheets? In these lecture notes, I attempt to provide the...