3 citations · 4 across the 4 of their papers we have counts for
4 papers
Neural Gaussian Similarity Modeling for Differential Graph Structure Learning
Xiaolong Fan, Maoguo Gong, Yue Wu +2
Graph Structure Learning (GSL) has demonstrated considerable potential in the analysis of graph-unknown non-Euclidean data across a wide range of domains. However, constructing an…
PCRDiffusion: Diffusion Probabilistic Models for Point Cloud Registration
Yue Wu, Yongzhe Yuan, Xiaolong Fan +3
We propose a new framework that formulates point cloud registration as a denoising diffusion process from noisy transformation to object transformation. During training stage, obje…
Towards Consistency and Complementarity: A Multiview Graph Information Bottleneck Approach
Xiaolong Fan, Maoguo Gong, Yue Wu +3
The empirical studies of Graph Neural Networks (GNNs) broadly take the original node feature and adjacency relationship as singleview input, ignoring the rich information of multip…
Maximizing Mutual Information Across Feature and Topology Views for Learning Graph Representations
Xiaolong Fan, Maoguo Gong, Yue Wu +1
Recently, maximizing mutual information has emerged as a powerful method for unsupervised graph representation learning. The existing methods are typically effective to capture inf…