5 citations · 7 across the 13 of their papers we have counts for
13 papers
COGENT: Continuous Graph Emulators with Neural Ordinary Differential Equations for Long-Term Physical Forecasting
Zesheng Liu, Maryam Rahnemoonfar
In this work, we present COGENT, a continuous graph emulator with Neural Ordinary Differential Equations for long-term physical forecasting on irregular geospatial meshes. COGENT e…
From Short Histories to Long Futures: Horizon-Aware Graph Neural Networks for Long Horizon Forecasting
Zesheng Liu, Maryam Rahnemoonfar
Accurate long-range prediction of geophysical systems is difficult due to strongly nonlinear dynamics, the high computational cost of full-physics simulations, and the error accumu…
DA-SegFormer: Damage-Aware Semantic Segmentation for Fine-Grained Disaster Assessment
Kevin Zhu, William Tang, Raphael Hay Tene +3
Rapid and accurate damage assessment following natural disasters is critical for effective emergency response. However, identifying fine-grained damage levels (e.g., distinguishing…
Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces
Zesheng Liu, Maryam Rahnemoonfar
Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often incomplete, with discontinuo…
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…
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…
GRIT-LP: Graph Transformer with Long-Range Skip Connection and Partitioned Spatial Graphs for Accurate Ice Layer Thickness Prediction
Zesheng Liu, Maryam Rahnemoonfar
Graph transformers have demonstrated remarkable capability on complex spatio-temporal tasks, yet their depth is often limited by oversmoothing and weak long-range dependency modeli…
KAN-GCN: Combining Kolmogorov-Arnold Network with Graph Convolution Network for an Accurate Ice Sheet Emulator
Zesheng Liu, YoungHyun Koo, Maryam Rahnemoonfar
We introduce KAN-GCN, a fast and accurate emulator for ice sheet modeling that places a Kolmogorov-Arnold Network (KAN) as a feature-wise calibrator before graph convolution networ…
ST-GRIT: Spatio-Temporal Graph Transformer For Internal Ice Layer Thickness Prediction
Zesheng Liu, Maryam Rahnemoonfar
Understanding the thickness and variability of internal ice layers in radar imagery is crucial for monitoring snow accumulation, assessing ice dynamics, and reducing uncertainties…
GRIT: Graph Transformer For Internal Ice Layer Thickness Prediction
Zesheng Liu, Maryam Rahnemoonfar
Gaining a deeper understanding of the thickness and variability of internal ice layers in Radar imagery is essential in monitoring the snow accumulation, better evaluating ice dyna…
Multi-branch Spatio-Temporal Graph Neural Network For Efficient Ice Layer Thickness Prediction
Zesheng Liu, Maryam Rahnemoonfar
Understanding spatio-temporal patterns in polar ice layers is essential for tracking changes in ice sheet balance and assessing ice dynamics. While convolutional neural networks ar…
Learning Spatio-Temporal Patterns of Polar Ice Layers With Physics-Informed Graph Neural Network
Zesheng Liu, Maryam Rahnemoonfar
Learning spatio-temporal patterns of polar ice layers is crucial for monitoring the change in ice sheet balance and evaluating ice dynamic processes. While a few researchers focus…
Physics-Informed Machine Learning On Polar Ice: A Survey
Zesheng Liu, YoungHyun Koo, Maryam Rahnemoonfar
The mass loss of the polar ice sheets contributes considerably to ongoing sea-level rise and changing ocean circulation, leading to coastal flooding and risking the homes and livel…