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DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Deep Graph Kernels

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A Local Algorithm for Structure-Preserving Graph Cut

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SPARC

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Learning Convolutional Neural Networks for Graphs

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Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering

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Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface

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Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs

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MINT: Detecting Fraudulent Behaviors from Time-Series Relational Data

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M2GNN: Multi-Scale Multi-Channel Graph Neural Network

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Towards Fine-Grained Temporal Network Representation via Time-Reinforced Random Walk

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GSSNN: Graph Smoothing Splines Neural Networks

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Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

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Data Augmentation for Graph Neural Networks

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On Generalized Degree Fairness in Graph Neural Networks

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Non-IID Transfer Learning on Graphs

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Tail-STEAK: Improve Friend Recommendation for Tail Users via Self-Training Enhanced Knowledge Distillation

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Incorporating Global Information in Local Attention for Knowledge Representation Learning

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Graph Partitioning for Lightweight Gnns: A Theoretical and Experimental Study

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M-Rgnn: A Robust Gnn Based on M-Estimators for Semi-Supervised Node Classification

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TailorNet: An Adaptive Collaborative Learning Framework for Imbalanced Multi-Relational Graphs via Tail Node Enhancement

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Survey of Network Embedding for Drug Analysis and Prediction

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Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

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MDGCN-Lt: Fair Web API Classification with Sparse and Heterogeneous Data Based on Deep GCN

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DAMGNN: Deep adaptive multi-channel graph neural networks

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Scalably Using Node Attributes and Graph Structure for Node Classification

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Generic Structure Extraction with Bi-Level Optimization for Graph Structure Learning

inferred← citeshttps://doi.org/10.3390/s23052398openalex-snapshot

Discrete Geodesic Distribution-Based Graph Kernel for 3D Point Clouds

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Relation Representation Learning via Signed Graph Mutual Information Maximization for Trust Prediction

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GraphDAFI: A graph representation learning framework with degree-aware feature interaction for node classification

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HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Network

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Simplification of Graph Convolutional Networks: A Matrix Factorization-based Perspective

inferred← citeshttps://doi.org/10.48550/arxiv.2010.11536openalex-snapshot

Joint Use of Node Attributes and Proximity for Semi-Supervised Classification on Graphs

inferred← citeshttps://doi.org/10.48550/arxiv.2012.13085openalex-snapshot

Semi-Supervised Node Classification on Graphs: Markov Random Fields vs. Graph Neural Networks

inferred← citeshttps://doi.org/10.48550/arxiv.2106.08640openalex-snapshot

Counterfactual Graphs for Explainable Classification of Brain Networks

inferred← citeshttps://doi.org/10.48550/arxiv.2107.01475openalex-snapshot

Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective

inferred← citeshttps://doi.org/10.5772/intechopen.111651openalex-snapshot

Graph Neural Networks and Reinforcement Learning: A Survey

inferred← citeshttps://doi.org/10.70675/a0861641z921cz48d8zb8a0z0830edcef2b8openalex-snapshot

Décimatiοn hiérarchique pοur l'apprentissage sur graphes

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