Hybrid framework predicts Arctic permafrost decline, risks infrastructure, and provides tools.
arXiv research
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Arctic coastal morphology is governed by multiple factors, many of which are affected by climatological changes. As the season length for shorefast ice decreases and temperatures warm permafrost soils, coastlines are more susceptible to erosion from storm waves. Such coastal erosion is a concern, since the majority of …
New method corrects seasonal Arctic sea ice predictions with probabilistic models.
Modeling vessel speed to balance efficiency and environmental risks in Arctic shipping.
Generative AI predicts Arctic sea ice dynamics over decades.
Most of the existing studies on voice conversion (VC) are conducted in acoustically matched conditions between source and target signal. However, the robustness of VC methods in presence of mismatch remains unknown. In this paper, we report a comparative analysis of different VC techniques under mismatched conditions. …
We consider the generalized Kahler structures (g,J_+,J_-) that arise on a hyperkahler manifold (M,g,I,J,K) when we choose J_+ and J_- from the twistor space of M. We find a relation between semichiral and arctic superfields which can be used to determine the generalized Kahler potential for hyperkahler manifolds whose …
Deep Learning is gaining traction with geophysics community to understand subsurface structures, such as fault detection or salt body in seismic data. This study describes using deep learning method for iceberg or ship recognition with synthetic aperture radar (SAR) data. Drifting icebergs pose a potential threat to ac…
The study uses machine learning to predict CAT bond coupons based on climate data.
End-to-end transformer model improves lexical stress detection accuracy.
New approach improves AI's handling of incomplete data.