90 citations · 220 across the 23 of their papers we have counts for
23 papers
Dual-modal Prior Semantic Guided Infrared and Visible Image Fusion for Intelligent Transportation System
Jing Li, Lu Bai, Bin Yang +4
Infrared and visible image fusion (IVF) plays an important role in intelligent transportation system (ITS). The early works predominantly focus on boosting the visual appeal of the…
SSHPool: The Separated Subgraph-based Hierarchical Pooling
Zhuo Xu, Lixin Cui, Ming Li +6
In this paper, we develop a novel local graph pooling method, namely the Separated Subgraph-based Hierarchical Pooling (SSHPool), for graph classification. We commence by assigning…
AKBR: Learning Adaptive Kernel-based Representations for Graph Classification
Feifei Qian, Lixin Cui, Ming Li +6
In this paper, we propose a new model to learn Adaptive Kernel-based Representations (AKBR) for graph classification. Unlike state-of-the-art R-convolution graph kernels that are d…
AERK: Aligned Entropic Reproducing Kernels through Continuous-time Quantum Walks
Lixin Cui, Ming Li, Yue Wang +2
In this work, we develop an Aligned Entropic Reproducing Kernel (AERK) for graph classification. We commence by performing the Continuous-time Quantum Walk (CTQW) on each graph str…
QESK: Quantum-based Entropic Subtree Kernels for Graph Classification
Lu Bai, Lixin Cui, Edwin R. Hancock
In this paper, we propose a novel graph kernel, namely the Quantum-based Entropic Subtree Kernel (QESK), for Graph Classification. To this end, we commence by computing the Average…
HAQJSK: Hierarchical-Aligned Quantum Jensen-Shannon Kernels for Graph Classification
Lu Bai, Lixin Cui, Yue Wang +2
In this work, we propose a family of novel quantum kernels, namely the Hierarchical Aligned Quantum Jensen-Shannon Kernels (HAQJSK), for un-attributed graphs. Different from most e…