AINeutralarXiv – CS AI · 18h ago6/10
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SRT: Super-Resolution for Time Series via Disentangled Rectified Flow
Researchers introduce SRT (Super-Resolution for Time Series), a novel AI framework using disentangled rectified flow to reconstruct high-resolution temporal data from low-resolution inputs. The method decomposes time series into trend and seasonal components, employs implicit neural representations, and includes a cross-resolution attention mechanism, with a scaled pre-trained version (SRT-large) demonstrating strong zero-shot capabilities across multiple datasets.