Summary of Incorporating Higher-order Structural Information For Graph Clustering, by Qiankun Li et al.
Incorporating Higher-order Structural Information for Graph Clusteringby Qiankun Li, Haobing Liu, Ruobing Jiang, Tingting WangFirst…
Incorporating Higher-order Structural Information for Graph Clusteringby Qiankun Li, Haobing Liu, Ruobing Jiang, Tingting WangFirst…
Functional Graph Convolutional Networks: A unified multi-task and multi-modal learning framework to facilitate health and…
Prediction of Vessel Arrival Time to Pilotage Area Using Multi-Data Fusion and Deep Learningby Xiaocai…
Hybrid Quantum-inspired Resnet and Densenet for Pattern Recognitionby Andi Chen, Hua-Lei Yin, Zeng-Bing Chen, Shengjun…
Self-Attention Empowered Graph Convolutional Network for Structure Learning and Node Embeddingby Mengying Jiang, Guizhong Liu,…
Rehabilitation Exercise Quality Assessment through Supervised Contrastive Learning with Hard and Soft Negativesby Mark Karlov,…
Deep Contrastive Graph Learning with Clustering-Oriented Guidanceby Mulin Chen, Bocheng Wang, Xuelong LiFirst submitted to…
Graph convolutional network as a fast statistical emulator for numerical ice sheet modelingby Maryam Rahnemoonfar,…
DS-MS-TCN: Otago Exercises Recognition with a Dual-Scale Multi-Stage Temporal Convolutional Networkby Meng Shang, Lenore Dedeyne,…
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction Recognitionby Mengyuan Liu, Chen Chen, Songtao Wu,…