How Powerful are Graph Neural Networks?

1 October 2018

Papers citing "How Powerful are Graph Neural Networks?"

50 / 1,174 papers shown

Title
Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment Xabier Echeberria-Barrio Amaia Gil-Lerchundi Jon Egana-Zubia Raul Orduna Urrutia AAML 24 6 0 12 Feb 2024
Continual Learning on Graphs: A Survey Zonggui Tian Duanhao Zhang Hong-Ning Dai 45 5 0 09 Feb 2024
Descriptive Kernel Convolution Network with Improved Random Walk Kernel Meng-Chieh Lee Lingxiao Zhao L. Akoglu 21 3 0 08 Feb 2024
Let Your Graph Do the Talking: Encoding Structured Data for LLMs Bryan Perozzi Bahare Fatemi Dustin Zelle Anton Tsitsulin Mehran Kazemi Rami Al-Rfou Jonathan J. Halcrow GNN 34 55 0 08 Feb 2024
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks Jiahua Rao Jiancong Xie Hanjing Lin Shuangjia Zheng Zhen Wang Yuedong Yang 21 0 0 07 Feb 2024
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers Md Shamim Hussain Mohammed J. Zaki D. Subramanian ViT 31 5 0 07 Feb 2024
Investigating Generalization Behaviours of Generative Flow Networks Lazar Atanackovic Emmanuel Bengio AI4CE 30 2 0 07 Feb 2024
On the Completeness of Invariant Geometric Deep Learning Models Zian Li Xiyuan Wang Shijia Kang Muhan Zhang 36 2 0 07 Feb 2024
Effective Protein-Protein Interaction Exploration with PPIretrieval Chenqing Hua Connor W. Coley Guy Wolf Doina Precup Shuangjia Zheng 30 3 0 06 Feb 2024
Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks Zhuomin Chen Jiaxing Zhang Jingchao Ni Xiaoting Li Yuchen Bian Md. Mezbahul Islam A. Mondal Hua Wei Dongsheng Luo 18 1 0 03 Feb 2024
Topology-Informed Graph Transformer Yuncheol Choi Sun Woo Park Minho Lee Youngho Woo 28 3 0 03 Feb 2024
DGNN: Decoupled Graph Neural Networks with Structural Consistency between Attribute and Graph Embedding Representations Jinlu Wang Jipeng Guo Yanfeng Sun Junbin Gao Shaofan Wang Yachao Yang Baocai Yin AI4CE 30 2 0 28 Jan 2024
Improving Expressive Power of Spectral Graph Neural Networks with Eigenvalue Correction Kangkang Lu Yanhua Yu Hao Fei Xuan Li Zixuan Yang Zirui Guo Meiyu Liang Mengran Yin Tat-Seng Chua 26 3 0 28 Jan 2024
Tensor-view Topological Graph Neural Network Tao Wen Elynn Chen Yuzhou Chen 34 9 0 22 Jan 2024
Towards Effective and General Graph Unlearning via Mutual Evolution Xunkai Li Yulin Zhao Zhengyu Wu Wentao Zhang Ronghua Li Guoren Wang MU 33 14 0 22 Jan 2024
FedGTA: Topology-aware Averaging for Federated Graph Learning Xunkai Li Zhengyu Wu Wentao Zhang Yinlin Zhu Ronghua Li Guoren Wang FedML 29 16 0 22 Jan 2024
Through the Dual-Prism: A Spectral Perspective on Graph Data Augmentation for Graph Classification Yutong Xia Runpeng Yu Yuxuan Liang Xavier Bresson Xinchao Wang Roger Zimmermann 37 4 0 18 Jan 2024
Disentangled Condensation for Large-scale Graphs Zhenbang Xiao Shunyu Liu Yu Wang Tongya Zheng Mingli Song Mingli Song Tongya Zheng DD 78 6 0 18 Jan 2024
Use of Graph Neural Networks in Aiding Defensive Cyber Operations Shaswata Mitra Trisha Chakraborty Subash Neupane Aritran Piplai Sudip Mittal AAML 42 3 0 11 Jan 2024
Explaining the Power of Topological Data Analysis in Graph Machine Learning Funmilola Mary Taiwo Umar Islambekov Cüneyt Gürcan Akçora AI4CE 36 3 0 08 Jan 2024
Effective backdoor attack on graph neural networks in link prediction tasks Jiazhu Dai Haoyu Sun GNN 59 3 0 05 Jan 2024
Graph Learning in 4D: a Quaternion-valued Laplacian to Enhance Spectral GCNs Stefano Fiorini Stefano Coniglio Michele Ciavotta Enza Messina GNN 29 5 0 28 Dec 2023
Molecular Property Prediction Based on Graph Structure Learning Bangyi Zhao Weixia Xu Jihong Guan Shuigeng Zhou 19 7 0 28 Dec 2023
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures Tianyi Zhang Haoteng Yin Rongzhe Wei Pan Li Anshumali Shrivastava AI4CE 23 1 0 28 Dec 2023
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching Federico Errica Henrik Christiansen Viktor Zaverkin Takashi Maruyama Mathias Niepert Francesco Alesiani 54 7 0 27 Dec 2023
Olfactory Label Prediction on Aroma-Chemical Pairs Laura Sisson Aryan Amit Barsainyan Mrityunjay Sharma Ritesh Kumar 11 0 0 26 Dec 2023
Molecular Hypergraph Neural Networks Junwu Chen Philippe Schwaller GNN 41 10 0 20 Dec 2023
Empowering Dual-Level Graph Self-Supervised Pretraining with Motif Discovery Pengwei Yan Kaisong Song Zhuoren Jiang Yangyang Kang Tianqianjin Lin Changlong Sun Xiaozhong Liu AI4CE 28 2 0 19 Dec 2023
Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization Tianrui Jia Haoyang Li Cheng Yang Tao Tao Chuan Shi OOD 33 17 0 18 Dec 2023
Label-Free Multivariate Time Series Anomaly Detection Qihang Zhou Shibo He Haoyu Liu Jiming Chen Wenchao Meng AI4TS 19 10 0 17 Dec 2023
Multi-agent Reinforcement Learning: A Comprehensive Survey Dom Huh Prasant Mohapatra AI4CE 30 8 0 15 Dec 2023
Curriculum-Enhanced Residual Soft An-Isotropic Normalization for Over-smoothness in Deep GNNs Jin Li Qirong Zhang Shuling Xu Xinlong Chen Longkun Guo Yanglan Fu 29 0 0 13 Dec 2023
HyPE-GT: where Graph Transformers meet Hyperbolic Positional Encodings Kushal Bose Swagatam Das 30 0 0 11 Dec 2023
Isomorphic-Consistent Variational Graph Auto-Encoders for Multi-Level Graph Representation Learning Hanxuan Yang Qingchao Kong Wenji Mao BDL 20 0 0 09 Dec 2023
Unsupervised Social Event Detection via Hybrid Graph Contrastive Learning and Reinforced Incremental Clustering Yuanyuan Guo Zehua Zang Hang Gao Xiao Xu Rui Wang Lixiang Liu Jiangmeng Li 26 5 0 08 Dec 2023
Enhancing Molecular Property Prediction via Mixture of Collaborative Experts Xu Yao Shuang Liang Songqiao Han Hailiang Huang 24 4 0 06 Dec 2023
NeutronStream: A Dynamic GNN Training Framework with Sliding Window for Graph Streams Chaoyi Chen Dechao Gao Yanfeng Zhang Qiange Wang Zhenbo Fu Xuecang Zhang Junhua Zhu Yu Gu Ge Yu GNN 35 5 0 05 Dec 2023
On the Trade-Off between Stability and Representational Capacity in Graph Neural Networks Zhan Gao Amanda Prorok Elvin Isufi 35 1 0 04 Dec 2023
Improving Self-supervised Molecular Representation Learning using Persistent Homology Yuankai Luo Lei Shi Veronika Thost SSL 34 8 0 29 Nov 2023
Metric Space Magnitude for Evaluating the Diversity of Latent Representations K. Limbeck R. Andreeva Rik Sarkar Bastian Alexander Rieck 22 3 0 27 Nov 2023
AdaMedGraph: Adaboosting Graph Neural Networks for Personalized Medicine Jie Lian Xufang Luo Caihua Shan Dongqi Han V. Vardhanabhuti Dongsheng Li 24 0 0 24 Nov 2023
HGCLIP: Exploring Vision-Language Models with Graph Representations for Hierarchical Understanding Peng Xia Xingtong Yu Ming Hu Lie Ju Zhiyong Wang Peibo Duan Zongyuan Ge VLM 54 9 0 23 Nov 2023
A Survey of Graph Meets Large Language Model: Progress and Future Directions Yuhan Li Zhixun Li Peisong Wang Jia Li Xiangguo Sun Hongtao Cheng Jeffrey Xu Yu 38 55 0 21 Nov 2023
Self-Supervised Pretraining for Heterogeneous Hypergraph Neural Networks Abdalgader Abubaker Takanori Maehara M. Nimishakavi Vassilis Plachouras SSL 45 0 0 19 Nov 2023
Correlation-Distance Graph Learning for Treatment Response Prediction from rs-fMRI Xiatian Zhang Sisi Zheng Hubert P. H. Shum Haozheng Zhang Nan Song Mingkang Song Hongxiao Jia 40 1 0 17 Nov 2023
Preserving Node-level Privacy in Graph Neural Networks Zihang Xiang Tianhao Wang Di Wang 25 6 0 12 Nov 2023
Going beyond persistent homology using persistent homology Johanna Immonen Amauri H. Souza Vikas K. Garg 31 9 0 10 Nov 2023
Mixture of Weak & Strong Experts on Graphs Hanqing Zeng Hanjia Lyu Diyi Hu Yinglong Xia Jiebo Luo 25 3 0 09 Nov 2023
Identifying Semantic Component for Robust Molecular Property Prediction Zijian Li Zunhong Xu Ruichu Cai Zhenhui Yang Yuguang Yan Zhifeng Hao Guan-Hong Chen Kun Zhang 23 9 0 08 Nov 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Lu Zhang Bo Han 37 3 0 02 Nov 2023