no code implementations • 6 Nov 2023 • Yao Cheng, Minjie Chen, Xiang Li, Caihua Shan, Ming Gao
Specifically, the framework consists of three components: a backbone GNN model, a propagation controller to determine the optimal propagation steps for nodes, and a weight controller to compute the priority scores for nodes.
1 code implementation • 15 Oct 2023 • Yueqi Ma, Minjie Chen, Xiang Li
Recently, Mixup has been introduced to synthesize hard negative samples in graph contrastive learning (GCL).
no code implementations • 5 Sep 2023 • Minjie Chen, Yao Cheng, Ye Wang, Xiang Li, Ming Gao
Further, Since the triplet loss only optimizes the relative distance between the anchor and its positive/negative samples, it is difficult to ensure the absolute distance between the anchor and positive sample.
no code implementations • 29 Jul 2023 • Mengyi Yuan, Minjie Chen, Xiang Li
Finally, an alternating training scheme is adopted to ensure that unsupervised node representation learning and information fusion controller can mutually reinforce each other.
no code implementations • 17 Feb 2023 • Zeliang Zhang, Jinyang Jiang, Minjie Chen, Zhiyuan Wang, Yijie Peng, Zhaofei Yu
Noise injection-based method has been shown to be able to improve the robustness of artificial neural networks in previous work.