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cs.LG2026
OPTNet: Ordering Point Transformer Network for Post-disaster 3D Semantic Segmentation
Nhut Le, Ehsan Karimi, Maryam Rahnemoonfar
Post-disaster damage assessment requires rapid and accurate semantic segmentation of 3D point clouds to identify critical infrastructure such as damaged buildings and roads. Early…
cs.LG2026
PACT: Peak-Aware Cross-Attention Graph Transformers for Efficient Storm-Surge Emulation
Zesheng Liu, Doyup Kwon, Ning Lin +1
Accurate and efficient storm-surge emulation is essential for coastal hazard assessment, yet high-fidelity hydrodynamic models remain too expensive for large scenario ensembles and…
cs.LG2026
K-STEMIT: Knowledge-Informed Spatio-Temporal Efficient Multi-Branch Graph Neural Network for Subsurface Stratigraphy Thickness Estimation from Radar Data
Zesheng Liu, Maryam Rahnemoonfar
Subsurface stratigraphy contains important spatio-temporal information about accumulation, deformation, and layer formation in polar ice sheets. In particular, variations in intern…