Zhonglin Huang

Dynamic Heterogeneous Graph Learning and Task-Conditioned Meta-Learning for Cold-Start Demand Forecasting in Multi-Warehouse Supply Chains

New products have little sales history, which makes short-horizon demand forecasting difficult. This study tests whether a product–store–time graph can provide pre-origin relational context and whether task-conditioned meta-learning can adapt a forecasting model from limited support observations. IGEML combines a dynam...