3 citations · 6 across the 2 of their papers we have counts for
3 papers
cond-mat.dis-nn2021★ 3 cited
Finding spin glass ground states through deep reinforcement learning
Changjun Fan, Mutian Shen, Zohar Nussinov +3
Spin glasses are disordered magnets with random interactions that are, generally, in conflict with each other. Finding the ground states of spin glasses is not only essential for t…
cs.SI2019
Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach
Changjun Fan, Li Zeng, Yuhui Ding +3
Betweenness centrality (BC) is one of the most used centrality measures for network analysis, which seeks to describe the importance of nodes in a network in terms of the fraction…
cs.LG2018★ 3 cited
VMAV-C: A Deep Attention-based Reinforcement Learning Algorithm for Model-based Control
Xingxing Liang, Qi Wang, Yanghe Feng +2
Recent breakthroughs in Go play and strategic games have witnessed the great potential of reinforcement learning in intelligently scheduling in uncertain environment, but some bott…