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Learning Subglacial Bed Topography from Sparse Radar with Physics-Guided Residuals
Bayu Adhi Tama, Jianwu Wang, Vandana Janeja +1
Accurate subglacial bed topography is essential for ice sheet modeling, yet radar observations are sparse and uneven. We propose a physics-guided residual learning framework that p…
Improving Greenland Bed Topography Mapping with Uncertainty-Aware Graph Learning on Sparse Radar Data
Bayu Adhi Tama, Homayra Alam, Mostafa Cham +3
Accurate maps of Greenland's subglacial bed are essential for sea-level projections, but radar observations are sparse and uneven. We introduce GraphTopoNet, a graph-learning frame…
DeepTopoNet: A Framework for Subglacial Topography Estimation on the Greenland Ice Sheets
Bayu Adhi Tama, Mansa Krishna, Homayra Alam +6
Understanding Greenland's subglacial topography is critical for projecting the future mass loss of the ice sheet and its contribution to global sea-level rise. However, the complex…
Assessing Annotation Accuracy in Ice Sheets Using Quantitative Metrics
Bayu Adhi Tama, Vandana Janeja, Sanjay Purushotham
The increasing threat of sea level rise due to climate change necessitates a deeper understanding of ice sheet structures. This study addresses the need for accurate ice sheet data…