3 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
HCPO: Hierarchical Conductor-Based Policy Optimization in Multi-Agent Reinforcement Learning
Zejiao Liu, Junqi Tu, Yitian Hong +4
In cooperative Multi-Agent Reinforcement Learning (MARL), efficient exploration is crucial for optimizing the performance of joint policy. However, existing methods often update jo…
DRAN: A Distribution and Relation Adaptive Network for Spatio-temporal Forecasting
Xiaobei Zou, Luolin Xiong, Kexuan Zhang +2
Spatio-temporal forecasting remains challenging under non-stationary environments because both data distributions and spatial relations evolve over time. Temporal normalization and…
SAMSGL: Series-Aligned Multi-Scale Graph Learning for Spatio-Temporal Forecasting
Xiaobei Zou, Luolin Xiong, Yang Tang +1
Spatio-temporal forecasting in various domains, like traffic prediction and weather forecasting, is a challenging endeavor, primarily due to the difficulties in modeling propagatio…
Interpretable Deep Reinforcement Learning for Optimizing Heterogeneous Energy Storage Systems
Luolin Xiong, Yang Tang, Chensheng Liu +4
Energy storage systems (ESS) are pivotal component in the energy market, serving as both energy suppliers and consumers. ESS operators can reap benefits from energy arbitrage by op…
Molecular Joint Representation Learning via Multi-modal Information
Tianyu Wu, Yang Tang, Qiyu Sun +1
In recent years, artificial intelligence has played an important role on accelerating the whole process of drug discovery. Various of molecular representation schemes of different…