"graph representation learning" Papers
48 papers found
Conference
A Deep Probabilistic Framework for Continuous Time Dynamic Graph Generation
Ryien Hosseini, Filippo Simini, Venkatram Vishwanath et al.
Bootstrapping Heterogeneous Graph Representation Learning via Large Language Models: A Generalized Approach
Hang Gao, Chenhao Zhang, Fengge Wu et al.
CaliGCL: Calibrated Graph Contrastive Learning via Partitioned Similarity and Consistency Discrimination
Yuena Lin, Hao Wei, Hai-Chun Cai et al.
Centrality-guided Pre-training for Graph
Bin Liang, Shiwei Chen, Lin Gui et al.
Cross-View Graph Consistency Learning for Invariant Graph Representations
Jie Chen, Hua Mao, Wai Lok Woo et al.
Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen, Yihong Luo, Yifan Song et al.
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Lequan Lin, Dai Shi, Andi Han et al.
Efficient Training of Neural Fractional-Order Differential Equation via Adjoint Backpropagation
Qiyu Kang, Xuhao Li, Kai Zhao et al.
Enhancing Graph Classification Robustness with Singular Pooling
Sofiane Ennadir, Oleg Smirnov, Yassine ABBAHADDOU et al.
Generative Graph Pattern Machine
Zehong Wang, Zheyuan Zhang, Tianyi Ma et al.
Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
Yifan Yang, Gang Chen, Hui Ma et al.
GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts
Zihao Guo, Qingyun Sun, Haonan Yuan et al.
GrokFormer: Graph Fourier Kolmogorov-Arnold Transformers
GUOGUO AI, Guansong Pang, Hezhe Qiao et al.
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec et al.
Learning Efficient Positional Encodings with Graph Neural Networks
Charilaos Kanatsoulis, Evelyn Choi, Stefanie Jegelka et al.
Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu et al.
Learning Long Range Dependencies on Graphs via Random Walks
Dexiong Chen, Till Schulz, Karsten Borgwardt
Learning Repetition-Invariant Representations for Polymer Informatics
Yihan Zhu, Gang Liu, Eric Inae et al.
MIHC: Multi-View Interpretable Hypergraph Neural Networks with Information Bottleneck for Chip Congestion Prediction
Zeyue Zhang, Heng Ping, Peiyu Zhang et al.
Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T Law et al.
OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
Juntong Wang, Xiyuan Wang, Muhan Zhang
On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation
Xinyu Ye, Hao Xiong, Jianhao Huang et al.
Random Search Neural Networks for Efficient and Expressive Graph Learning
Michael Ito, Danai Koutra, Jenna Wiens
Revisiting Graph Contrastive Learning on Anomaly Detection: A Structural Imbalance Perspective
Yiming Xu, Zhen Peng, Bin Shi et al.
SOLA-GCL: Subgraph-Oriented Learnable Augmentation Method for Graph Contrastive Learning
Tianhao Peng, Xuhong Li, Haitao Yuan et al.
SONAR: Long-Range Graph Propagation Through Information Waves
Alessandro Trenta, Alessio Gravina, Davide Bacciu
Spectro-Riemannian Graph Neural Networks
Karish Grover, Haiyang Yu, Xiang song et al.
SSTAG: Structure-Aware Self-Supervised Learning Method for Text-Attributed Graphs
Ruyue Liu, Rong Yin, Xiangzhen Bo et al.
The quest for the GRAph Level autoEncoder (GRALE)
Paul Krzakala, Gabriel Melo, Charlotte Laclau et al.
TopER: Topological Embeddings in Graph Representation Learning
Astrit Tola, Funmilola Mary Taiwo, Cuneyt Akcora et al.
UniGTE: Unified Graph–Text Encoding for Zero-Shot Generalization across Graph Tasks and Domains
Duo Wang, Yuan Zuo, Guangyue Lu et al.
A Graph is Worth $K$ Words: Euclideanizing Graph using Pure Transformer
Zhangyang Gao, Daize Dong, Cheng Tan et al.
Community-Invariant Graph Contrastive Learning
Shiyin Tan, Dongyuan Li, Renhe Jiang et al.
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Chow, Yifei Sun et al.
From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang et al.
Graph As Point Set
Xiyuan Wang, Pan Li, Muhan Zhang
Graph External Attention Enhanced Transformer
Jianqing Liang, Min Chen, Jiye Liang
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
HGAP: Boosting Permutation Invariant and Permutation Equivariant in Multi-Agent Reinforcement Learning via Graph Attention Network
Bor Jiun Lin, Chun-Yi Lee
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction
Kangkang Lu, Yanhua Yu, Hao Fei et al.
Learning Divergence Fields for Shift-Robust Graph Representations
Qitian Wu, Fan Nie, Chenxiao Yang et al.
Learning Graph Representation via Graph Entropy Maximization
Ziheng Sun, Xudong Wang, Chris Ding et al.
PC-Conv: Unifying Homophily and Heterophily with Two-Fold Filtering
Bingheng Li, Erlin Pan, Zhao Kang
Position: Relational Deep Learning - Graph Representation Learning on Relational Databases
Matthias Fey, Weihua Hu, Kexin Huang et al.
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou, Tolga Birdal, Michael Bronstein et al.
Recurrent Distance Filtering for Graph Representation Learning
Yuhui Ding, Antonio Orvieto, Bobby He et al.
TopoGCL: Topological Graph Contrastive Learning
Yuzhou Chen, Jose Frias, Yulia Gel
Union Subgraph Neural Networks
Jiaxing Xu, Aihu Zhang, Qingtian Bian et al.