GraphFLEx: Structure Learning Framework for Large Expanding Graphs | Paper Citation Record

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This paper cites Graph neural networks: A review of methods and applications,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph neural networks: A review of methods and applications,

Reference 1

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Observation 168be2ec-83f2-403d-9e45-f53603063322 · outbound

This paper cites Protein interface prediction using graph convo- lutional networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Protein interface prediction using graph convo- lutional networks,

Reference 2

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This paper cites Graph convolutional networks with markov random field reasoning for social spammer detection,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph convolutional networks with markov random field reasoning for social spammer detection,

Reference 3

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This paper cites Hyperdefender: A robust framework for hyperbolic gnns,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Hyperdefender: A robust framework for hyperbolic gnns,

Reference 4

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This paper cites Scene graph generation with external knowledge and image reconstruction,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Scene graph generation with external knowledge and image reconstruction,

Reference 5

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Observation d28a1919-eba6-4234-b0f6-53f4123789e9 · outbound

This paper cites A Survey on Graph Structure Learning: Progress and Opportunities.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs A Survey on Graph Structure Learning: Progress and Opportunities

Reference 6

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This paper cites Comparing statistical methods for constructing large scale gene networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Comparing statistical methods for constructing large scale gene networks,

Reference 7

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This paper cites Towards unsupervised deep graph structure learning,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Towards unsupervised deep graph structure learning,

Reference 8

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Observation 3a4a36aa-4fe0-46c5-be56-1e5ada1aff8e · outbound

This paper cites Graph neural networks: Graph structure learning,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph neural networks: Graph structure learning,

Reference 9

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Observation 32a7c2ec-66c3-4f69-b77e-58e3ce839c7e · outbound

This paper cites Nodeformer: A scalable graph structure learning transformer for node classification,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Nodeformer: A scalable graph structure learning transformer for node classification,

Reference 10

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Observation 659f52c4-c745-4f2a-a338-aa149590be4d · outbound

This paper cites Graph structure learning for robust graph neural networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph structure learning for robust graph neural networks,

Reference 11

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This paper cites Variational inference for training graph neural networks in low-data regime through joint structure-label estimation,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Variational inference for training graph neural networks in low-data regime through joint structure-label estimation,

Reference 12

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This paper cites Slaps: Self-supervision improves structure learning for graph neural networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Slaps: Self-supervision improves structure learning for graph neural networks,

Reference 13

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This paper cites Efficient k-nearest neighbor graph construction for generic similarity measures,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Efficient k-nearest neighbor graph construction for generic similarity measures,

Reference 14

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This paper cites Scalable nearest neighbor algorithms for high dimensional data,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Scalable nearest neighbor algorithms for high dimensional data,

Reference 15

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This paper cites Some methods for classification and analysis of multivariate observations,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Some methods for classification and analysis of multivariate observations,

Reference 16

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This paper cites Label propagation through linear neighborhoods,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Label propagation through linear neighborhoods,

Reference 17

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This paper cites Sparse inverse covariance matrix esti- mation using quadratic approximation,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Sparse inverse covariance matrix esti- mation using quadratic approximation,

Reference 18

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This paper cites Sparse inverse covariance estimation with the graphical lasso,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Sparse inverse covariance estimation with the graphical lasso,

Reference 19

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Observation a9eabcdf-310e-44f4-9334-f3b3692c7ac5 · outbound

This paper cites Learning laplacian matrix in smooth graph signal representations,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Learning laplacian matrix in smooth graph signal representations,

Reference 20

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This paper cites How to learn a graph from smooth signals,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs How to learn a graph from smooth signals,

Reference 21

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This paper cites A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation

Reference 22

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This paper cites Community detection in graphs,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Community detection in graphs,

Reference 23

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This paper cites Graph clustering with graph neural networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph clustering with graph neural networks,

Reference 24

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This paper cites Spectral learning,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Spectral learning,

Reference 25

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This paper cites Constrained k-means clustering with background knowledge,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Constrained k-means clustering with background knowledge,

Reference 26

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Observation 36c9686e-2d25-4a3b-b565-feb466c7177c · outbound

This paper cites Spectral Networks and Locally Connected Networks on Graphs.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Spectral Networks and Locally Connected Networks on Graphs

Reference 27

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This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Convolutional neural networks on graphs with fast localized spectral filtering,

Reference 28

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This paper cites Graph reduction with spectral and cut guarantees.,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph reduction with spectral and cut guarantees.,

Reference 29

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This paper cites Linear complexity framework for feature-aware graph coarsening via hashing,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Linear complexity framework for feature-aware graph coarsening via hashing,

Reference 30

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This paper cites A unified framework for optimization-based graph coarsening,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs A unified framework for optimization-based graph coarsening,

Reference 31

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This paper cites UGC: Universal graph coarsening,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs UGC: Universal graph coarsening,

Reference 32

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This paper cites Semi-supervised learning using gaussian fields and harmonic functions,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Semi-supervised learning using gaussian fields and harmonic functions,

Reference 33

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This paper cites Koller and N.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Koller and N

Reference 34

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This paper cites Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Model selection through sparse maximum likelihood estimation for multivariate gaussian or binary data,

Reference 35

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This paper cites Covariance selection,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Covariance selection,

Reference 36

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This paper cites Manifold regularization: A geometric framework for learning from labeled and unlabeled examples.,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Manifold regularization: A geometric framework for learning from labeled and unlabeled examples.,

Reference 37

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This paper cites A graph theoretical regression model for brain connectivity learning of alzheimer’s disease,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs A graph theoretical regression model for brain connectivity learning of alzheimer’s disease,

Reference 38

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This paper cites Three scenarios for continual learning.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Three scenarios for continual learning

Reference 39

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This paper cites Cglb: Benchmark tasks for continual graph learning,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Cglb: Benchmark tasks for continual graph learning,

Reference 40

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This paper cites Continual lifelong learning with neural networks: A review,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Continual lifelong learning with neural networks: A review,

Reference 41

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This paper cites Dygrain: An incremental learning framework for dynamic graphs.,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Dygrain: An incremental learning framework for dynamic graphs.,

Reference 42

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This paper cites Continual graph convolutional network for text classification,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Continual graph convolutional network for text classification,

Reference 43

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This paper cites Roland: graph learning framework for dynamic graphs,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Roland: graph learning framework for dynamic graphs,

Reference 44

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This paper cites Temporal recommendation on graphs via long-and short-term preference fusion,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Temporal recommendation on graphs via long-and short-term preference fusion,

Reference 45

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This paper cites Microsoft academic graph: When experts are not enough,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Microsoft academic graph: When experts are not enough,

Reference 46

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This paper cites Spectral clustering with graph neural networks for graph pooling,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Spectral clustering with graph neural networks for graph pooling,

Reference 47

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This paper cites Simplifying Clustering with Graph Neural Networks.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Simplifying Clustering with Graph Neural Networks

Reference 48

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This paper cites Modularity and community structure in networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Modularity and community structure in networks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:43.321077Z

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This paper cites Consistency of community detection in networks under degree-corrected stochastic block models,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Consistency of community detection in networks under degree-corrected stochastic block models,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:43.309916Z

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This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Semi-Supervised Classification with Graph Convolutional Networks

Reference 51

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This paper cites Inductive representation learning on large graphs,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Inductive representation learning on large graphs,

Reference 52

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This paper cites How Powerful are Graph Neural Networks?.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs How Powerful are Graph Neural Networks?

Reference 53

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This paper cites Graph attention networks,.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph attention networks,

Reference 54

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Observation d41d32cb-86ee-4450-ae52-aed3bafa8f4d · outbound

This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.

GraphFLEx: Structure Learning Framework for Large Expanding Graphs GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 55

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs The extreme classification repository: Multi-label datasets and code,

Reference 56

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Conductance and the rapid mixing property for markov chains: the approximation of permanent resolved,

Reference 57

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Visualizing structure and transitions in high-dimensional biological data,

Reference 58

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Mnist handwritten digit database,

Reference 59

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Glove: Global vectors for word representation,

Reference 60

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs An information flow model for conflict and fission in small groups,

Reference 61

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Locality-sensitive hashing scheme based on p-stable distributions,

Reference 62

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Link prediction in complex networks: A survey,

Reference 63

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph classification using signal-subgraphs: Applications in statistical connectomics,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:43.188077Z

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Graph Condensation for Graph Neural Networks

Reference 65

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Revisiting semi-supervised learning with graph embeddings,

Reference 66

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Pitfalls of Graph Neural Network Evaluation

Reference 67

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Magnn: Metapath aggregated graph neural network for heterogeneous graph embedding,

Reference 68

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs scbert as a large-scale pretrained deep language model for cell type annotation of single-cell rna-seq data,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:42:43.134849Z

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Pygsp: Graph signal processing in python

Reference 70

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Collective dynamics of ‘small-world’networks,

Reference 71

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GraphFLEx: Structure Learning Framework for Large Expanding Graphs Unresolved cited work

Reference 2020

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