Poster "graph representation learning" Papers
18 papers found
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Lequan Lin, Dai Shi, Andi Han et al.
Learning Graph Invariance by Harnessing Spuriosity
Tianjun Yao, Yongqiang Chen, Kai Hu et al.
Random Search Neural Networks for Efficient and Expressive Graph Learning
Michael Ito, Danai Koutra, Jenna Wiens
SONAR: Long-Range Graph Propagation Through Information Waves
Alessandro Trenta, Alessio Gravina, Davide Bacciu
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.
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
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.
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.