9 citations · 17 across the 11 of their papers we have counts for
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cs.LG2023
Exploring Sparsity in Graph Transformers
Chuang Liu, Yibing Zhan, Xueqi Ma +5
Graph Transformers (GTs) have achieved impressive results on various graph-related tasks. However, the huge computational cost of GTs hinders their deployment and application, espe…
cs.LG2023
Careful Selection and Thoughtful Discarding: Graph Explicit Pooling Utilizing Discarded Nodes
Chuang Liu, Wenhang Yu, Kuang Gao +5
Graph pooling has been increasingly recognized as crucial for Graph Neural Networks (GNNs) to facilitate hierarchical graph representation learning. Existing graph pooling methods…
cs.LG2023
On Exploring Node-feature and Graph-structure Diversities for Node Drop Graph Pooling
Chuang Liu, Yibing Zhan, Baosheng Yu +4
A pooling operation is essential for effective graph-level representation learning, where the node drop pooling has become one mainstream graph pooling technology. However, current…