Proves that rescaled deviations of kernel gradient flow and infinitesimal gradient boosting from their deterministic ODE limits converge to a Gaussian process via a general stochastic perturbation analysis of ODEs in Banach spaces.
Journal of spatial information science , 1–17
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
ProbGLC unifies probabilistic and deterministic geolocalization models to deliver state-of-the-art accuracy (0.86 Acc@1km) plus uncertainty quantification on multi-disaster cross-view datasets.
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Towards Generative Location Awareness for Disaster Response: A Probabilistic Cross-view Geolocalization Approach
ProbGLC unifies probabilistic and deterministic geolocalization models to deliver state-of-the-art accuracy (0.86 Acc@1km) plus uncertainty quantification on multi-disaster cross-view datasets.