1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2024
Deep Hierarchical Graph Alignment Kernels
Shuhao Tang, Hao Tian, Xiaofeng Cao +1
Typical R-convolution graph kernels invoke the kernel functions that decompose graphs into non-isomorphic substructures and compare them. However, overlooking implicit similarities…
cs.LG2024★ 1 cited
COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems
Hao Tian, Sourav Medya, Wei Ye
Combinatorial Optimization (CO) problems over graphs appear routinely in many applications such as in optimizing traffic, viral marketing in social networks, and matching for job a…
cs.CV2023
PICNN: A Pathway towards Interpretable Convolutional Neural Networks
Wengang Guo, Jiayi Yang, Huilin Yin +2
Convolutional Neural Networks (CNNs) have exhibited great performance in discriminative feature learning for complex visual tasks. Besides discrimination power, interpretability is…