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Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly encode higher-order topology, such as ring systems and recurring motifs. Existing higher-order representations can capture these structures directly, but they are often...
Heat Kernel Textures (HKTex) eliminate UV unwrapping as well as their persistent issues of wasted UV space, seams, distortions, vertex-duplication, and varying resolution.
A station-guided framework for high-resolution PM downscaling over Europe that recovers fine-grained spatial structures and effectively mitigates localised CAMS biases and introduces a time-agnostic propagation strategy that utilises spatial Gaussian blending of interpolated OpenAQ observations.
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