Federated Contrastive Learning of Graph-Level Representations | Paper Citation Record

Observation 03d6f700-896f-48d6-a56f-1cafec0addd3 · outbound

This paper cites Survey of graph database models,.

Federated Contrastive Learning of Graph-Level Representations Survey of graph database models,

Reference 1

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This paper cites Cgnn: Traffic classification with graph neural network,.

Federated Contrastive Learning of Graph-Level Representations Cgnn: Traffic classification with graph neural network,

Reference 2

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Observation 559bdfab-b79d-4e71-94cc-41d7eb0a73f3 · outbound

This paper cites Traffic classification based on graph convolutional network,.

Federated Contrastive Learning of Graph-Level Representations Traffic classification based on graph convolutional network,

Reference 3

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Observation d256d21d-fa67-46b3-88da-9d45b450fb58 · outbound

This paper cites Learned protein embeddings for machine learning,.

Federated Contrastive Learning of Graph-Level Representations Learned protein embeddings for machine learning,

Reference 4

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Observation 5f8cdeac-c9a5-450a-9ba7-b0fac5a6e5d8 · outbound

This paper cites Structure-based protein function prediction using graph convolutional networks,.

Federated Contrastive Learning of Graph-Level Representations Structure-based protein function prediction using graph convolutional networks,

Reference 5

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Observation f614c2b7-4803-4d36-a23c-36c160827eac · outbound

This paper cites Comparison of descriptor spaces for chemical compound retrieval and classification,.

Federated Contrastive Learning of Graph-Level Representations Comparison of descriptor spaces for chemical compound retrieval and classification,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:32.058727Z

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Observation d2abc580-49d2-4866-8cd0-5c584d54e0e8 · outbound

This paper cites Moleculenet: A benchmark for molecular machine learning,.

Federated Contrastive Learning of Graph-Level Representations Moleculenet: A benchmark for molecular machine learning,

Reference 7

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Observation 07030edc-e33e-4d1f-b0db-9e8eec89199d · outbound

This paper cites Utilizing graph machine learning within drug discovery and development,.

Federated Contrastive Learning of Graph-Level Representations Utilizing graph machine learning within drug discovery and development,

Reference 8

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Observation 9db9caf3-3dd1-4d70-acec-46fc89954ea3 · outbound

This paper cites Could graph neural networks learn better molecular representation for drug discovery? a comparison study of descriptor- based and graph-based models.

Federated Contrastive Learning of Graph-Level Representations Could graph neural networks learn better molecular representation for drug discovery? a comparison study of descriptor- based and graph-based models

Reference 9

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Observation 12bc2458-093e-472d-bfe2-8cd6efc455fb · outbound

This paper cites Tactilegcn: A graph convolutional network for predicting grasp stability with tactile sensors,.

Federated Contrastive Learning of Graph-Level Representations Tactilegcn: A graph convolutional network for predicting grasp stability with tactile sensors,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.999392Z

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Observation 9aefe722-30d0-4b92-92e3-97e6efd5e779 · outbound

This paper cites Towards Federated Graph Learning for Collaborative Financial Crimes Detection.

Federated Contrastive Learning of Graph-Level Representations Towards Federated Graph Learning for Collaborative Financial Crimes Detection

Reference 11

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Observation a8a443fc-e474-427f-8aa5-1168a98bf48f · outbound

This paper cites Fedgnn: Federated graph neural network for privacy-preserving recommendation,.

Federated Contrastive Learning of Graph-Level Representations Fedgnn: Federated graph neural network for privacy-preserving recommendation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.985055Z

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Observation e0a1ed58-ce52-46de-82a6-64acde24cbec · outbound

This paper cites Subgraph federated learning with missing neighbor generation,.

Federated Contrastive Learning of Graph-Level Representations Subgraph federated learning with missing neighbor generation,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.971402Z

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Observation fd3048f6-2297-4bc6-b5f3-b6bf387e92b3 · outbound

This paper cites Federated myopic community detection with one-shot communication,.

Federated Contrastive Learning of Graph-Level Representations Federated myopic community detection with one-shot communication,

Reference 14

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Observation b52539a0-cd47-4fdf-b360-3e6a21951ff9 · outbound

This paper cites Communication-efficient learning of deep networks from decentralized data,.

Federated Contrastive Learning of Graph-Level Representations Communication-efficient learning of deep networks from decentralized data,

Reference 15

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Observation 06144413-6fce-43ca-9c16-4b8e3fa9b1e8 · outbound

This paper cites Federated Graph Classification over Non-IID Graphs.

Federated Contrastive Learning of Graph-Level Representations Federated Graph Classification over Non-IID Graphs

Reference 16

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Observation 601c89eb-840e-4099-8caf-33381577223d · outbound

This paper cites Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches,.

Federated Contrastive Learning of Graph-Level Representations Facing small and biased data dilemma in drug discovery with enhanced federated learning approaches,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.927388Z

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Observation c6e5c221-8457-401e-8a4b-c87666d323c9 · outbound

This paper cites Nf-gnn: network flow graph neural networks for malware detection and classification,.

Federated Contrastive Learning of Graph-Level Representations Nf-gnn: network flow graph neural networks for malware detection and classification,

Reference 18

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Observation 0c772ad0-e346-4829-ac85-6a283be267d3 · outbound

This paper cites Infograph: Unsupervised and semi-supervised graph-level representation learning via mutual information maximization,.

Federated Contrastive Learning of Graph-Level Representations Infograph: Unsupervised and semi-supervised graph-level representation learning via mutual information maximization,

Reference 19

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Observation f26aa66a-1c44-49e4-bd15-bd3e833f528f · outbound

This paper cites Density functional theory,.

Federated Contrastive Learning of Graph-Level Representations Density functional theory,

Reference 20

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Observation e6c357a3-079e-4f18-9661-02bbf890229e · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Federated Contrastive Learning of Graph-Level Representations Semi-supervised classification with graph convolutional networks,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.865759Z

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Observation 53d12274-cb72-4037-a716-eeb842ea78a2 · outbound

This paper cites How powerful are graph neural networks?.

Federated Contrastive Learning of Graph-Level Representations How powerful are graph neural networks?

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.850395Z

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Observation 4a66fb9e-08e8-4c10-8578-9f2bac91e065 · outbound

This paper cites An end- to-end deep learning architecture for graph classification,.

Federated Contrastive Learning of Graph-Level Representations An end- to-end deep learning architecture for graph classification,

Reference 23

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Observation aed5c17d-1cd3-46cf-96a4-7c2be52faab4 · outbound

This paper cites Hierarchical graph representation learning with differentiable pooling,.

Federated Contrastive Learning of Graph-Level Representations Hierarchical graph representation learning with differentiable pooling,

Reference 24

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Observation 1bec20f2-61e9-4b83-8670-548e5fd36c02 · outbound

This paper cites graph2vec: Learning Distributed Representations of Graphs.

Federated Contrastive Learning of Graph-Level Representations graph2vec: Learning Distributed Representations of Graphs

Reference 25

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Observation b1745f27-e281-4d9f-9c74-99e45f71ac8b · outbound

This paper cites Strategies for Pre-training Graph Neural Networks.

Federated Contrastive Learning of Graph-Level Representations Strategies for Pre-training Graph Neural Networks

Reference 26

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Observation cca6ac06-ed60-4cbf-b80d-88a27f7599ce · outbound

This paper cites Biological network comparison using graphlet degree distri- bution,.

Federated Contrastive Learning of Graph-Level Representations Biological network comparison using graphlet degree distri- bution,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.805268Z

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Observation 27473ad5-2950-479f-860c-222f0aa30684 · outbound

This paper cites Graph invariant kernels,.

Federated Contrastive Learning of Graph-Level Representations Graph invariant kernels,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.790691Z

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Observation 6c63ec47-cc80-4d45-9d3a-8212a04fefca · outbound

This paper cites Contrastive multi-view representa- tion learning on graphs,.

Federated Contrastive Learning of Graph-Level Representations Contrastive multi-view representa- tion learning on graphs,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.776170Z

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Observation f560f4fd-46ee-4d6c-95ec-2694d077c88e · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Federated Contrastive Learning of Graph-Level Representations A simple framework for contrastive learning of visual representations,

Reference 30

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This paper cites Learning word embeddings efficiently with noise-contrastive estimation,.

Federated Contrastive Learning of Graph-Level Representations Learning word embeddings efficiently with noise-contrastive estimation,

Reference 31

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Observation 30cc5106-a55b-4f7a-b1a4-72b815a1ebc3 · outbound

This paper cites Model-contrastive federated learning,.

Federated Contrastive Learning of Graph-Level Representations Model-contrastive federated learning,

Reference 32

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Observation bff39497-237b-462f-bc08-6e464265b9b8 · outbound

This paper cites FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning.

Federated Contrastive Learning of Graph-Level Representations FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning

Reference 33

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Observation 32c68ee5-7a00-4ee7-930c-91e53fb4b5c7 · outbound

This paper cites Federated Unsupervised Representation Learning.

Federated Contrastive Learning of Graph-Level Representations Federated Unsupervised Representation Learning

Reference 34

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Observation 396e56e4-5984-4744-98fb-4978f54de76f · outbound

This paper cites Ensemble distillation for robust model fusion in federated learning,.

Federated Contrastive Learning of Graph-Level Representations Ensemble distillation for robust model fusion in federated learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.729216Z

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Observation b5cc4dc5-3db8-4e96-a061-833be4cd940a · outbound

This paper cites Comparing kullback- leibler divergence and mean squared error loss in knowledge distilla- tion,.

Federated Contrastive Learning of Graph-Level Representations Comparing kullback- leibler divergence and mean squared error loss in knowledge distilla- tion,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.714148Z

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Observation 08174ad5-5a94-4cfd-aac9-4c9e68b1c22e · outbound

This paper cites Fast subtree kernels on graphs,.

Federated Contrastive Learning of Graph-Level Representations Fast subtree kernels on graphs,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.696542Z

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Observation 08db4752-7e8e-48eb-9420-606fe1948517 · outbound

This paper cites Graph kernels,.

Federated Contrastive Learning of Graph-Level Representations Graph kernels,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.678357Z

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Observation 304c3d4c-e1f0-4c72-bfb5-348ce25d5343 · outbound

This paper cites Deep graph kernels,.

Federated Contrastive Learning of Graph-Level Representations Deep graph kernels,

Reference 39

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Observation 0aa5241f-ce29-4cb4-a3a1-96978f18a479 · outbound

This paper cites Node, motif and subgraph: Leveraging network functional blocks through structural convolution,.

Federated Contrastive Learning of Graph-Level Representations Node, motif and subgraph: Leveraging network functional blocks through structural convolution,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.640770Z

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Observation cce95cce-1363-4066-93ba-2cc13a1ee22b · outbound

This paper cites Learning deep representations by mutual information estimation and maximization,.

Federated Contrastive Learning of Graph-Level Representations Learning deep representations by mutual information estimation and maximization,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.622711Z

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Observation 7b61bd9a-4e94-43f9-9359-31dbf74646fe · outbound

This paper cites Contrastive multiview coding,.

Federated Contrastive Learning of Graph-Level Representations Contrastive multiview coding,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.603103Z

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Observation bf1ca972-d21a-4bfe-acaa-cf126224495c · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective,.

Federated Contrastive Learning of Graph-Level Representations Improved deep metric learning with multi-class n-pair loss objective,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.584657Z

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Observation feb81784-cd94-492f-9391-a4fa84be7089 · outbound

This paper cites Unsupervised feature learning via non-parametric instance discrimination,.

Federated Contrastive Learning of Graph-Level Representations Unsupervised feature learning via non-parametric instance discrimination,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.563636Z

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Observation 384e9f34-cebc-4004-9fef-aa34f3453e88 · outbound

This paper cites Gcc: Graph contrastive coding for graph neural network pre- training,.

Federated Contrastive Learning of Graph-Level Representations Gcc: Graph contrastive coding for graph neural network pre- training,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.546374Z

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Observation 59966ff9-88fb-4dfc-a2dd-c7891ebf87f8 · outbound

This paper cites Collaborative unsupervised visual representation learning from decentralized data,.

Federated Contrastive Learning of Graph-Level Representations Collaborative unsupervised visual representation learning from decentralized data,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.531107Z

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Observation ae4b8a67-14f0-42a0-974d-34d14153c3eb · outbound

This paper cites FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks.

Federated Contrastive Learning of Graph-Level Representations FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks

Reference 47

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Observation 464fdf26-8862-43e8-96fa-8bca842b77cb · outbound

This paper cites Spreadgnn: Serverless multi-task federated learning for graph neural networks,.

Federated Contrastive Learning of Graph-Level Representations Spreadgnn: Serverless multi-task federated learning for graph neural networks,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.515877Z

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Observation 2818e80c-c981-4195-9417-3b017477bca9 · outbound

This paper cites Born again neural networks,.

Federated Contrastive Learning of Graph-Level Representations Born again neural networks,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.501804Z

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Observation fcfe77c6-363b-4645-a47d-e31df2d5f051 · outbound

This paper cites Understanding and Improving Knowledge Distillation.

Federated Contrastive Learning of Graph-Level Representations Understanding and Improving Knowledge Distillation

Reference 50

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Source-reported events for the cited work

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Observation 89394aca-2c2c-4481-909a-668d82cc299b · outbound

This paper cites Diffusion Improves Graph Learning.

Federated Contrastive Learning of Graph-Level Representations Diffusion Improves Graph Learning

Reference 51

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Observation 590f3522-52bb-48ff-8de3-458cec657666 · outbound

This paper cites Representation learning on graphs with jumping knowledge networks,.

Federated Contrastive Learning of Graph-Level Representations Representation learning on graphs with jumping knowledge networks,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-12T17:59:30.949756Z

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Observation 2367d88d-7446-4125-844e-a7f39b050a31 · outbound

This paper cites Protein function prediction via graph kernels,.

Federated Contrastive Learning of Graph-Level Representations Protein function prediction via graph kernels,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.478370Z

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Observation 5cbcc172-7d9f-4db7-920f-209595ce1ae8 · outbound

This paper cites Spline-fitting with a genetic algorithm: a method for developing classification structure- activity relationships,.

Federated Contrastive Learning of Graph-Level Representations Spline-fitting with a genetic algorithm: a method for developing classification structure- activity relationships,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.463972Z

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Observation 23c0fc8b-0ceb-42dc-aba3-bbfb38bf7c66 · outbound

This paper cites Comparison of descriptor spaces for chemical compound retrieval and classification,.

Federated Contrastive Learning of Graph-Level Representations Comparison of descriptor spaces for chemical compound retrieval and classification,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:59:31.447863Z

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Observation e024d2f2-e97a-4909-910e-ff348e252f5c · outbound

This paper cites TUDataset: A collection of benchmark datasets for learning with graphs.

Federated Contrastive Learning of Graph-Level Representations TUDataset: A collection of benchmark datasets for learning with graphs

Reference 56

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This paper cites Fast graph representation learning with PyTorch Geometric,.

Federated Contrastive Learning of Graph-Level Representations Fast graph representation learning with PyTorch Geometric,

Reference 57

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Federated Contrastive Learning of Graph-Level Representations Decoupled weight decay regularization,

Reference 58

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Federated Contrastive Learning of Graph-Level Representations Scikit-learn: Machine learning in Python,

Reference 59

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Federated Contrastive Learning of Graph-Level Representations Federated optimization in heterogeneous networks,

Reference 60

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This paper cites A metric for distributions with applications to image databases,.

Federated Contrastive Learning of Graph-Level Representations A metric for distributions with applications to image databases,

Reference 61

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This paper cites Federated visual classification with real-world data distribution,.

Federated Contrastive Learning of Graph-Level Representations Federated visual classification with real-world data distribution,

Reference 62

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Federated Contrastive Learning of Graph-Level Representations A k-means clustering algorithm,

Reference 63

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This paper cites Accelerating t-sne using tree-based algorithms,.

Federated Contrastive Learning of Graph-Level Representations Accelerating t-sne using tree-based algorithms,

Reference 64

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