"graph neural networks" Papers
308 papers found • Page 3 of 7
Conference
Memorization in Graph Neural Networks
Adarsh Jamadandi, Jing Xu, Adam Dziedzic et al.
Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
Zinan Zheng, Yang Liu, Jia Li
MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
Paul Garnier, Vincent Lannelongue, Jonathan Viquerat et al.
Meta Flow Matching: Integrating Vector Fields on the Wasserstein Manifold
Lazar Atanackovic, Xi (Nicole) Zhang, Brandon Amos et al.
ML4CO-Bench-101: Benchmark Machine Learning for Classic Combinatorial Problems on Graphs
Jiale Ma, Wenzheng Pan, Yang Li et al.
Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation
Jun Hu, Bryan Hooi, Bingsheng He et al.
MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights
Jingjing Hu, Dan Guo, Zhan Si et al.
Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment
Shuo Wang, Bokui Wang, Zhixiang Shen et al.
Multi-order Orchestrated Curriculum Distillation for Model-Heterogeneous Federated Graph Learning
Guancheng Wan, Xu Cheng, Run Liu et al.
NN-Former: Rethinking Graph Structure in Neural Architecture Representation
Ruihan Xu, Haokui Zhang, Yaowei Wang et al.
Node Identifiers: Compact, Discrete Representations for Efficient Graph Learning
Yuankai Luo, Hongkang Li, Qijiong Liu et al.
Node-Time Conditional Prompt Learning in Dynamic Graphs
Xingtong Yu, Zhenghao Liu, Xinming Zhang et al.
Noisy Node Classification by Bi-level Optimization Based Multi-Teacher Distillation
Yujing Liu, Zongqian Wu, Zhengyu Lu et al.
Normalize Then Propagate: Efficient Homophilous Regularization for Few-Shot Semi-Supervised Node Classification
Baoming Zhang, MingCai Chen, Jianqing Song et al.
Novel Class Discovery for Point Cloud Segmentation via Joint Learning of Causal Representation and Reasoning
Yang Li, Aming WU, Zihao Zhang et al.
Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction
KunHo Heo, GiHyun Kim, SuYeon Kim 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.
One Prompt Fits All: Universal Graph Adaptation for Pretrained Models
Yongqi Huang, Jitao Zhao, Dongxiao He et al.
On Logic-based Self-Explainable Graph Neural Networks
Alessio Ragno, Marc Plantevit, Céline Robardet
On the Hölder Stability of Multiset and Graph Neural Networks
Yair Davidson, Nadav Dym
On Transferring Transferability: Towards a Theory for Size Generalization
Eitan Levin, Yuxin Ma, Mateo Diaz et al.
Open-Set Cross-Network Node Classification via Unknown-Excluded Adversarial Graph Domain Alignment
Xiao Shen, Zhihao Chen, Shirui Pan et al.
Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction
Yanbin Wei, Xuehao Wang, Zhan Zhuang et al.
Personalized Image Editing in Text-to-Image Diffusion Models via Collaborative Direct Preference Optimization
Connor Dunlop, Matthew Zheng, Kavana Venkatesh et al.
PF∆: A Benchmark Dataset for Power Flow under Load, Generation, and Topology Variations
Ana Rivera Him, Anvita Bhagavathula, Alvaro Carbonero et al.
PointRWKV: Efficient RWKV-Like Model for Hierarchical Point Cloud Learning
Qingdong He, Jiangning Zhang, Jinlong Peng et al.
PolyhedronNet: Representation Learning for Polyhedra with Surface-attributed Graph
Dazhou Yu, Genpei Zhang, Liang Zhao
Practical Bayes-Optimal Membership Inference Attacks
Marcus Lassila, Johan Oestman, Khac-Hoang Ngo et al.
PRAGA: Prototype-aware Graph Adaptive Aggregation for Spatial Multi-modal Omics Analysis
Xinlei Huang, Zhiqi Ma, Dian Meng et al.
Predicting the Energy Landscape of Stochastic Dynamical System via Physics-informed Self-supervised Learning
Ruikun Li, Huandong Wang, Qingmin Liao et al.
Preference-driven Knowledge Distillation for Few-shot Node Classification
Xing Wei, Chunchun Chen, Rui Fan et al.
ProfiX: Improving Profile-Guided Optimization in Compilers with Graph Neural Networks
Huiri Tan, Juyong Jiang, Jiasi Shen
Prompt-based Unifying Inference Attack on Graph Neural Networks
Yuecen Wei, Xingcheng Fu, Lingyun Liu et al.
Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization
Yang Qiu, Yixiong Zou, Jun Wang et al.
RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases
Dongwon Choi, Sunwoo Kim, Juyeon Kim et al.
REBIND: Enhancing Ground-state Molecular Conformation Prediction via Force-Based Graph Rewiring
Taewon Kim, Hyunjin Seo, Sungsoo Ahn et al.
Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
Steve Azzolin, Antonio Longa, Stefano Teso et al.
Refining Norms: A Post-hoc Framework for OOD Detection in Graph Neural Networks
Jiawei Gu, Ziyue Qiao, Zechao Li
Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization
Lirong Wu, Haitao Lin, Yufei Huang et al.
RelGNN: Composite Message Passing for Relational Deep Learning
Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec
REM: A Scalable Reinforced Multi-Expert Framework for Multiplex Influence Maximization
Huyen Nguyen, Hieu Dam, Nguyen Hoang Khoi Do et al.
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Michael Scholkemper, Xinyi Wu, Ali Jadbabaie et al.
Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features
Feng Ji, Yanan Zhao, KAI ZHAO et al.
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.
RIGNO: A Graph-based Framework For Robust And Accurate Operator Learning For PDEs On Arbitrary Domains
Sepehr Mousavi, Shizheng Wen, Levi Lingsch 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.
Sample complexity of data-driven tuning of model hyperparameters in neural networks with structured parameter-dependent dual function
Maria-Florina Balcan, Anh Nguyen, Dravyansh Sharma