Time series foundation models are becoming increasingly popular for general-purpose forecasting. However, most leading models predict marginal quantiles, leaving the dependence structure of future trajectories unspecified. This distinction matters for trajectory-dependent quantities such as cumulative demand, peak load...
Jia-Chen Yao, Xi-Yuan Zhang, An-Nan Yu et al.· 0 citations
Structured data drives enterprise decision-making, yet building predictive pipelines for time-series and tabular modalities requires intensive feature engineering, model selection, and other ''tricks of the trade''. AutoGluon, an open source AutoML system, automates this through multi-layer stack ensembling, providing...
Boran Han, Nick Erickson, Abdul Fatir Ansari et al.· Proceedings of the 32nd ACM...· 0 citations
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