35 citations · 56 across the 6 of their papers we have counts for
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cs.LG2024
Transform then Explore: a Simple and Effective Technique for Exploratory Combinatorial Optimization with Reinforcement Learning
Tianle Pu, Changjun Fan, Mutian Shen +5
Many complex problems encountered in both production and daily life can be conceptualized as combinatorial optimization problems (COPs) over graphs. Recent years, reinforcement lea…
cs.LG2023★ 2 cited
Machine Learning for the Multi-Dimensional Bin Packing Problem: Literature Review and Empirical Evaluation
Wenjie Wu, Changjun Fan, Jincai Huang +2
The Bin Packing Problem (BPP) is a well-established combinatorial optimization (CO) problem. Since it has many applications in our daily life, e.g. logistics and resource allocatio…
cs.LG2023★ 35 cited
The Expressive Power of Graph Neural Networks: A Survey
Bingxu Zhang, Changjun Fan, Shixuan Liu +4
Graph neural networks (GNNs) are effective machine learning models for many graph-related applications. Despite their empirical success, many research efforts focus on the theoreti…