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cs.LG2026
One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning
Bowen He, Juncheng Dong, Lin Lin +1
A central challenge in reinforcement learning (RL) is to learn models that generalize beyond the tasks on which they are trained, a goal traditionally pursued through multi-task an…
cs.LG2026
Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning
Umme Mahbuba Nabila, Paul Seurin, Linyu Lin +1
Real-time supervisory control of thermal energy distribution systems requires digital twins that are accurate, interpretable, and uncertainty-aware, yet remain data and computation…