All in One and One for All: A Simple yet Effective Method towards
Cross-domain Graph Pretraining

All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining

15 February 2024

Papers citing "All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining"

11 / 11 papers shown

Title
Enhancing Graph Self-Supervised Learning with Graph Interplay Xinjian Zhao Wei Pang Xiangru Jian Yaoyao Xu Chaolong Ying Tianshu Yu 45 0 0 17 Jan 2025
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation Kexin Zhang Shuhan Liu Song Wang Weili Shi Chen Chen Pan Li Sheng R. Li Jundong Li Kaize Ding OOD 45 2 0 25 Oct 2024
Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning Zinan Zheng Yang Liu Jia Li Jianhua Yao Yu Rong AI4CE 38 1 0 24 Jun 2024
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment Haihong Zhao Chenyi Zi Yang Liu Chen Zhang Yan Zhou Jia Li 28 7 0 06 Feb 2024
Semi-supervised Domain Adaptation in Graph Transfer Learning Ziyue Qiao Xiao Luo Meng Xiao Hao Dong Yuanchun Zhou Hui Xiong OOD 58 21 0 19 Sep 2023
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey Huali Xu Shuaifeng Zhi Shuzhou Sun Vishal M. Patel Li Liu 23 13 0 15 Mar 2023
Rethinking Graph Neural Networks for Anomaly Detection Jianheng Tang Jiajin Li Zi-Chao Gao Jia Li 67 193 0 31 May 2022
Community Question Answering Entity Linking via Leveraging Auxiliary Data Yuhan Li Wei Shen Jianbo Gao Yadong Wang 27 10 0 24 May 2022
ImageNet-21K Pretraining for the Masses T. Ridnik Emanuel Ben-Baruch Asaf Noy Lihi Zelnik-Manor SSeg VLM CLIP 154 676 0 22 Apr 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 84 554 0 04 Jan 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 167 1,058 0 13 Feb 2020