"graph neural networks" Papers
188 papers found • Page 2 of 4
Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks
Chenyi Zi, Bowen LIU, Xiangguo SUN et al.
Rethinking the role of frames for SE(3)-invariant crystal structure modeling
Yusei Ito, Tatsunori Taniai, Ryo Igarashi et al.
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade et al.
RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs
Xi Xie, Yuebo Luo, Hongwu Peng et al.
SignFlow Bipartite Subgraph Network For Large-Scale Graph Link Sign Prediction
Yixiao Zhou, Xiaoqing Lyu, Hongxiang Lin et al.
SINGER: Stochastic Network Graph Evolving Operator for High Dimensional PDEs
Mingquan Feng, Yixin Huang, Weixin Liao et al.
S'MoRE: Structural Mixture of Residual Experts for Parameter-Efficient LLM Fine-tuning
Hanqing Zeng, Yinglong Xia, Zhuokai Zhao et al.
SONAR: Long-Range Graph Propagation Through Information Waves
Alessandro Trenta, Alessio Gravina, Davide Bacciu
Spreading Out-of-Distribution Detection on Graphs
Daeho Um, Jongin Lim, Sunoh Kim et al.
SSTAG: Structure-Aware Self-Supervised Learning Method for Text-Attributed Graphs
Ruyue Liu, Rong Yin, Xiangzhen Bo et al.
The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited
Floriano Tori, Vincent Holst, Vincent Ginis
The Logical Expressiveness of Temporal GNNs via Two-Dimensional Product Logics
Marco Sälzer, Przemyslaw Walega, Martin Lange
Towards a Complete Logical Framework for GNN Expressiveness
Tuo Xu
Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations
Richard Bergna, Sergio Calvo Ordoñez, Felix Opolka et al.
Unsupervised Federated Graph Learning
Lele Fu, Tianchi Liao, Sheng Huang et al.
Valid Conformal Prediction for Dynamic GNNs
Ed Davis, Ian Gallagher, Daniel Lawson et al.
When GNNs meet symmetry in ILPs: an orbit-based feature augmentation approach
Qian Chen, Lei Li, Qian Li et al.
A Generalized Neural Diffusion Framework on Graphs
10011 Yibo Li, Xiao Wang, Hongrui Liu et al.
A Graph Dynamics Prior for Relational Inference
Liming Pan, Cheng Shi, Ivan Dokmanic
Aligning Transformers with Weisfeiler-Leman
Luis Müller, Christopher Morris
An Empirical Study of Realized GNN Expressiveness
Yanbo Wang, Muhan Zhang
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, KAI WU, Xiaoyu Zhang et al.
Bounded and Uniform Energy-based Out-of-distribution Detection for Graphs
Shenzhi Yang, Bin Liang, An Liu et al.
Cell Graph Transformer for Nuclei Classification
Wei Lou, Guanbin Li, Xiang Wan et al.
Collective Certified Robustness against Graph Injection Attacks
Yuni Lai, Bailin PAN, kaihuang CHEN et al.
COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems
Hao Tian, Sourav Medya, Wei Ye
Cooperative Graph Neural Networks
Ben Finkelshtein, Xingyue Huang, Michael Bronstein et al.
Coupling Graph Neural Networks with Fractional Order Continuous Dynamics: A Robustness Study
Qiyu Kang, Kai Zhao, Yang Song et al.
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-Smoothness in Deep GNNs
Jin Li, Qirong Zhang, Shuling Xu et al.
Delaunay Graph: Addressing Over-Squashing and Over-Smoothing Using Delaunay Triangulation
Hugo Attali, Davide Buscaldi, Nathalie Pernelle
DGCLUSTER: A Neural Framework for Attributed Graph Clustering via Modularity Maximization
Aritra Bhowmick, Mert Kosan, Zexi Huang et al.
DiffDA: a Diffusion model for weather-scale Data Assimilation
Langwen Huang, Lukas Gianinazzi, Yuejiang Yu et al.
Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization
Haoyang Li, Xin Wang, Zeyang Zhang et al.
DOGE-Train: Discrete Optimization on GPU with End-to-End Training
Ahmed Abbas, P. Swoboda
EiG-Search: Generating Edge-Induced Subgraphs for GNN Explanation in Linear Time
Shengyao Lu, Bang Liu, Keith Mills et al.
Empowering Graph Invariance Learning with Deep Spurious Infomax
Tianjun Yao, Yongqiang Chen, Zhenhao Chen et al.
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
Zheng Huang, Qihui Yang, Dawei Zhou et al.
Every Node Is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering
Pengfei Zhu, Qian Wang, Yu Wang et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc Bui, Trung Hieu Nguyen, Viet Anh Nguyen et al.
Expressivity and Generalization: Fragment-Biases for Molecular GNNs
Tom Wollschläger, Niklas Kemper, Leon Hetzel et al.
Extending Test-Time Augmentation with Metamorphic Relations for Combinatorial Problems
Siwei Wei, Xudong Zhang, Zhiyang Zhou et al.
Fact-Driven Logical Reasoning for Machine Reading Comprehension
Siru Ouyang, Zhuosheng Zhang, Hai Zhao
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
Cheng Yang, Jixi Liu, Yunhe Yan et al.
Feature Distribution on Graph Topology Mediates the Effect of Graph Convolution: Homophily Perspective
Soo Yong Lee, Sunwoo Kim, Fanchen Bu et al.
Federated Self-Explaining GNNs with Anti-shortcut Augmentations
Linan Yue, Qi Liu, Weibo Gao et al.
Fine-Tuning Graph Neural Networks by Preserving Graph Generative Patterns
Yifei Sun, Qi Zhu, Yang Yang et al.
Finite Volume Features, Global Geometry Representations, and Residual Training for Deep Learning-based CFD Simulation
Loh S.E. Jessica, Naheed Anjum Arafat, Wei Xian Lim 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.
From Geometry to Causality- Ricci Curvature and the Reliability of Causal Inference on Networks
Amirhossein Farzam, Allen Tannenbaum, Guillermo Sapiro