3 papers
cs.LG2026
TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting
Lingyu Jiang, Lingyu Xu, Peiran Li +14
We propose TimePre, a simple framework that unifies the efficiency of Multilayer Perceptron (MLP)-based models with the distributional flexibility of Multiple Choice Learning (MCL)…
cs.LG2026
KANMixer: a minimal KAN-centered mixer for long-term time series forecasting
Lingyu Jiang, Dengzhe Hou, Yuping Wang +9
Long-term time series forecasting (LTSF) underpins critical applications from energy management to weather prediction, yet achieving reliable multi-step-ahead accuracy remains chal…
cs.LG2026
Multi-Agent Reinforcement Learning with Submodular Reward
Wenjing Chen, Chengyuan Qian, Shuo Xing +2
In this paper, we study cooperative multi-agent reinforcement learning (MARL) where the joint reward exhibits submodularity, which is a natural property capturing diminishing margi…