CONVERT: Contrastive Graph Clustering with Reliable Augmentation
暂无分享,去创建一个
Stan Z. Li | Yue Liu | Siwei Wang | Jun Xia | Cheng Tan | Xihong Yang | Sihang Zhou | Xinwang Liu | En Zhu | K. Liang
[1] Shifei Ding,et al. Graph clustering network with structure embedding enhanced , 2023, Pattern Recognition.
[2] Zaixin Zhang,et al. A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design , 2023, ArXiv.
[3] Stan Z. Li,et al. Dink-Net: Neural Clustering on Large Graphs , 2023, ICML.
[4] Yue Liu,et al. Message Intercommunication for Inductive Relation Reasoning , 2023, ArXiv.
[5] Zaixin Zhang,et al. Learning Subpocket Prototypes for Generalizable Structure-based Drug Design , 2023, ICML.
[6] Chang-Yu Hsieh,et al. An equivariant generative framework for molecular graph-structure Co-design , 2023, bioRxiv.
[7] Xiaolei Huang,et al. ABSLearn: a GNN-based framework for aliasing and buffer-size information retrieval , 2023, Pattern Analysis and Applications.
[8] Xihong Yang,et al. Self-Supervised Temporal Graph learning with Temporal and Structural Intensity Alignment , 2023, ArXiv.
[9] Shirui Pan,et al. Neighbor Contrastive Learning on Learnable Graph Augmentation , 2023, AAAI Conference on Artificial Intelligence.
[10] Yue Liu,et al. Cluster-guided Contrastive Graph Clustering Network , 2023, AAAI.
[11] Yue Liu,et al. Hard Sample Aware Network for Contrastive Deep Graph Clustering , 2022, AAAI.
[12] Yue Liu,et al. Contrastive Deep Graph Clustering with Learnable Augmentation , 2022, ArXiv.
[13] Stan Z. Li,et al. A Survey of Deep Graph Clustering: Taxonomy, Challenge, and Application , 2022, ArXiv.
[14] Jiaming Wu,et al. Embedding Global and Local Influences for Dynamic Graphs , 2022, CIKM.
[15] Jiliang Tang,et al. Test-Time Training for Graph Neural Networks , 2022, ArXiv.
[16] Sihang Zhou,et al. Attributed Graph Clustering with Dual Redundancy Reduction , 2022, IJCAI.
[17] Defu Lian,et al. Cooperative Retriever and Ranker in Deep Recommenders , 2022, WWW.
[18] Yue Liu,et al. Mixed Graph Contrastive Network for Semi-Supervised Node Classification , 2022, ACM Transactions on Knowledge Discovery from Data.
[19] Enhong Chen,et al. Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever , 2022, NeurIPS.
[20] Siwei Wang,et al. Simple Contrastive Graph Clustering , 2022, IEEE transactions on neural networks and learning systems.
[21] Min Lin,et al. Causal Representation Learning for Out-of-Distribution Recommendation , 2022, WWW.
[22] Enhong Chen,et al. Learning Recommenders for Implicit Feedback with Importance Resampling , 2022, WWW.
[23] Yue Liu,et al. Improved Dual Correlation Reduction Network , 2022, ArXiv.
[24] En Zhu,et al. Interpolation-based Contrastive Learning for Few-Label Semi-Supervised Learning , 2022, IEEE transactions on neural networks and learning systems.
[25] Stan Z. Li,et al. SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation , 2022, WWW.
[26] Hao Peng,et al. Towards Unsupervised Deep Graph Structure Learning , 2022, WWW.
[27] En Zhu,et al. Deep Graph Clustering via Dual Correlation Reduction , 2021, AAAI.
[28] Xinzhong Zhu,et al. Fast Parameter-Free Multi-View Subspace Clustering With Consensus Anchor Guidance , 2021, IEEE Transactions on Image Processing.
[29] Chanyoung Park,et al. Augmentation-Free Self-Supervised Learning on Graphs , 2021, AAAI.
[30] En Zhu,et al. Late Fusion Multiple Kernel Clustering With Proxy Graph Refinement , 2021, IEEE Transactions on Neural Networks and Learning Systems.
[31] Siyu Huang,et al. AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators , 2021, AAAI.
[32] Enhong Chen,et al. Fast Variational AutoEncoder with Inverted Multi-Index for Collaborative Filtering , 2021, WWW.
[33] Wei Jin,et al. Localized Graph Collaborative Filtering , 2021, SDM.
[34] Han Zhao,et al. Graph Debiased Contrastive Learning with Joint Representation Clustering , 2021, IJCAI.
[35] Meng Liu,et al. Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences , 2021, SIGIR.
[36] Xiaorui Liu,et al. Automated Self-Supervised Learning for Graphs , 2021, ICLR.
[37] Zhangyang Wang,et al. Graph Contrastive Learning Automated , 2021, ICML.
[38] Jennifer Neville,et al. Adversarial Graph Augmentation to Improve Graph Contrastive Learning , 2021, NeurIPS.
[39] Bryan Hooi,et al. Mixup for Node and Graph Classification , 2021, WWW.
[40] Jieren Cheng,et al. Deep Fusion Clustering Network , 2020, AAAI.
[41] Qiang Liu,et al. Graph Contrastive Learning with Adaptive Augmentation , 2020, WWW.
[42] Xiangliang Zhang,et al. SAIL: Self-Augmented Graph Contrastive Learning , 2020, AAAI.
[43] Bryan Hooi,et al. NodeAug: Semi-Supervised Node Classification with Data Augmentation , 2020, KDD.
[44] Jie Zhou,et al. Adaptive Graph Encoder for Attributed Graph Embedding , 2020, KDD.
[45] Kaveh Hassani,et al. Contrastive Multi-View Representation Learning on Graphs , 2020, ICML.
[46] Xiao Wang,et al. Structural Deep Clustering Network , 2020, WWW.
[47] Noel E. O'Connor,et al. Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning , 2019, 2020 International Joint Conference on Neural Networks (IJCNN).
[48] Yun Fu,et al. Adversarial Graph Embedding for Ensemble Clustering , 2019, IJCAI.
[49] Jing Jiang,et al. Attributed Graph Clustering: A Deep Attentional Embedding Approach , 2019, IJCAI.
[50] Chengqi Zhang,et al. Learning Graph Embedding With Adversarial Training Methods , 2019, IEEE Transactions on Cybernetics.
[51] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[52] Qianqian Wang,et al. Self-consistent Contrastive Attributed Graph Clustering with Pseudo-label Prompt , 2022, IEEE Transactions on Multimedia.
[53] Yue Liu,et al. Reasoning over Different Types of Knowledge Graphs: Static, Temporal and Multi-Modal , 2022, ArXiv.
[54] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[55] Shie Mannor,et al. A Tutorial on the Cross-Entropy Method , 2005, Ann. Oper. Res..