3 papers
stat.AP2026
Multi-objective probabilistic forecast combination for inventory demand
Shengjie Wang, Yanfei Kang, Evangelos Spiliotis +1
Probabilistic forecasts are essential for inventory management, where decisions depend on the full distribution of future demand. While probabilistic forecast combination is widely…
stat.ML2026
REGAIN: REconciliation GAIN-driven Auxiliary Direction Learning
Weijia Li, Shun Hu, Yanfei Kang
Forecast reconciliation usually starts from a fixed measurement system and asks how forecasts should be projected onto a coherent space. We ask a different question: which addition…
cs.AI2025
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…