no code implementations • 20 Oct 2021 • Chenggang Cui, Tianxiao Yang, Yuxuan Dai, Chuanlin Zhang
Reinforcement learning (RL) control approach with application into power electronics systems has become an emerging topic whilst the sim-to-real issue remains a challenging problem as very few results can be referred to in the literature.
1 code implementation • 24 Feb 2021 • Ke-Jia Chen, Jiajun Zhang, Linpu Jiang, Yunyun Wang, Yuxuan Dai
This paper proposes a pre-training method on dynamic graph neural networks (PT-DGNN), which uses dynamic attributed graph generation tasks to simultaneously learn the structure, semantics, and evolution features of the graph.