Poster "graph neural networks" Papers
208 papers found • Page 2 of 5
Conference
Greener GRASS: Enhancing GNNs with Encoding, Rewiring, and Attention
Tongzhou Liao, Barnabás Póczos
Higher-Order Graphon Neural Networks: Approximation and Cut Distance
Daniel Herbst, Stefanie Jegelka
Higher-Order Learning with Graph Neural Networks via Hypergraph Encodings
Raphaël Pellegrin, Lukas Fesser, Melanie Weber
Holographic Node Representations: Pre-training Task-Agnostic Node Embeddings
Beatrice Bevilacqua, Joshua Robinson, Jure Leskovec et al.
Homomorphism Expressivity of Spectral Invariant Graph Neural Networks
Jingchu Gai, Yiheng Du, Bohang Zhang et al.
Hypergraph Vision Transformers: Images are More than Nodes, More than Edges
Joshua Fixelle
Improving Graph Neural Networks by Learning Continuous Edge Directions
Seong Ho Pahng, Sahand Hormoz
InversionGNN: A Dual Path Network for Multi-Property Molecular Optimization
Yifan Niu, Ziqi Gao, Tingyang Xu et al.
Iterative Substructure Extraction for Molecular Relational Learning with Interactive Graph Information Bottleneck
Shuai Zhang, Junfeng Fang, Xuqiang Li et al.
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
Learning Efficient Positional Encodings with Graph Neural Networks
Charilaos Kanatsoulis, Evelyn Choi, Stefanie Jegelka 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.
Learning to Plan Like the Human Brain via Visuospatial Perception and Semantic-Episodic Synergistic Decision-Making
Tianyuan Jia, Ziyu Li, Qing Li et al.
Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
Yilun Zheng, Xiang Li, Sitao Luan et al.
Logical Expressiveness of Graph Neural Networks with Hierarchical Node Individualization
Arie Soeteman, Balder ten Cate
MAGE: Model-Level Graph Neural Networks Explanations via Motif-based Graph Generation
Zhaoning Yu, Hongyang Gao
Making Classic GNNs Strong Baselines Across Varying Homophily: A Smoothness–Generalization Perspective
Ming Gu, Zhuonan Zheng, Sheng Zhou et al.
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
Wenxuan Bao, Zhichen Zeng, Zhining Liu et al.
MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
Carlo Abate, Filippo Maria Bianchi
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.
ML4CO-Bench-101: Benchmark Machine Learning for Classic Combinatorial Problems on Graphs
Jiale Ma, Wenzheng Pan, Yang Li 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.
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
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.
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.
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
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
RelGNN: Composite Message Passing for Relational Deep Learning
Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec
Residual Connections and Normalization Can Provably Prevent Oversmoothing in GNNs
Michael Scholkemper, Xinyi Wu, Ali Jadbabaie et al.