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Fully Automated Correlated Time Series Forecasting in Minutes

Summary: Fully automated framework for correlated time-series forecasting that uses data-driven iterative pruning of human search spaces, zero-shot model search, and fast parameter adaptation to enable search and training in minutes. Matches or beats SOTA on seven benchmarks while dramatically reducing search/training time. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13811
Venue
VLDB
Year
2025
Pagerank
-
Overall Rank
13,113 | 8.78%
DOI
10.14778/3705829.3705835

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