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Precipitation nowcasting, generating future radar fields from past observations, is critical for flood warning and disaster response. It is also a demanding benchmark for spatiotemporal generative modeling, with chaotic dynamics, heavy-tailed intensities, and rare high-intensity structures that matter most. Determinist...
This study aims to accurately predict students’ academic performance trajectories for university entrance examinations by proposing a machine learning framework that explicitly accounts for missing data and uncertainty. Mock examination data are characterized by substantial missing values due to heterogeneous participa...
A controlled SASRec variant is studied that replaces learned attention weights with uniform aggregation and is trained under an otherwise identical block structure and training recipe, and this modification often yields performance comparable to the original model, with clear dataset-dependent exceptions.
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