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Structural Deep Clustering Network

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01264-9_9openalex-snapshot

Deep Clustering for Unsupervised Learning of Visual Features

inferredcites →https://doi.org/10.1016/0377-0427(87)90125-7openalex-snapshot

Silhouettes: A graphical aid to the interpretation and validation of cluster analysis

inferredcites →https://doi.org/10.1109/access.2018.2830661openalex-snapshot

A Survey of Deep Learning: Platforms, Applications and Emerging Research Trends

inferredcites →https://doi.org/10.1109/tip.2010.2049235openalex-snapshot

Image Clustering Using Local Discriminant Models and Global Integration

inferredcites →https://doi.org/10.1109/tpami.2018.2794976openalex-snapshot

Metric Learning for Multi-Output Tasks

inferredcites →https://doi.org/10.1145/1390156.1390294openalex-snapshot

Extracting and composing robust features with denoising autoencoders

inferredcites →https://doi.org/10.1145/2809695.2809718openalex-snapshot

Smart Devices are Different

inferredcites →https://doi.org/10.1145/3308558.3313562openalex-snapshot

Heterogeneous Graph Attention Network

inferredcites →https://doi.org/10.24963/ijcai.2017/273openalex-snapshot

Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering

inferredcites →https://doi.org/10.24963/ijcai.2019/509openalex-snapshot

Attributed Graph Clustering: A Deep Attentional Embedding Approach

inferredcites →https://doi.org/10.5555/1005332.1005345openalex-snapshot

RCV1: A New Benchmark Collection for Text Categorization Research

inferredcites →https://doi.org/10.5555/3122009.3176825openalex-snapshot

Making decision trees feasible in ultrahigh feature and label dimensions

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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DCOM-GNN: A Deep Clustering Optimization Method for Graph

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Adaptive Information Random Consistency Clustering Network

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Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas

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Localized Global Time Series Forecasting Models Using Evolutionary Neighbor‐Aided Deep Clustering Method

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Inductive Document Representation Learning for Short Text Clustering

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Representation Learning for Short Text Clustering

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Knowledge Integration in Deep Clustering

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NE-WNA: A Novel Network Embedding Framework Without Neighborhood Aggregation

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Contrastive Learning with Cluster-Preserving Augmentation for Attributed Graph Clustering

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Deep Friendly Embedding Space for Clustering

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A Novel Deep Clustering Approach to Assess Dominance Between Solutions of a Multi-objective Optimization Problem

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Distance-Guided Pseudo Label Graph Clustering Network

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Entropy-Guided Graph Clustering via Rényi Optimization

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CS$$^2$$C: Collaborative Spatial and Spectral Neural Clustering for Organelle Segmentation from Volumetric Electron Microscopy

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Deep Graph Clustering Using Graph Neural Networks and Seed Detection

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Contrastive Deep Graph Clustering with Dynamic Cluster Estimation

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Deep Structured Clustering of Short Text

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Feature Fusion-Based Attribute Graph Clustering

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Structured Variational Graph Clustering with Attention Mechanism

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GUIDE: Learnable Deep Contrastive Graph Clustering with Centrality Guidance

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Enhancing Behavior Expression Through Behavioral Structure

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Improving the Louvain Algorithm in Community Detection

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Dual Contrastive Attributed Graph Clustering with Adaptive Structure

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High-Order Structure Enhanced Graph Clustering Network

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Depth-Enhanced Contrast Attribute Graph Clustering

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Graph Fusion Based Autoencoder for Node Clustering

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An Efficient Low-Pass Contrastive Graph Clustering Network for Hyperspectral Images

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Adaptive Homophily Clustering for Hyperspectral Image

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Multi-scale Multi-order Attributed Graph Clustering

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Scalable Deep Metric Learning on Attributed Graphs

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Unsupervised Conversation Disentanglement with GCN Clustering

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SEGCN: Structural Enhancement Graph Clustering Network

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Structure and Semantic Contrastive Learning for Nodes Clustering in Heterogeneous Information Networks

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Deep Learning-Based Attribute Graph Clustering: An Overview

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Incorporating Higher-order Structural Information for Graph Clustering

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Node Embedding Enhancement Model Based on Joint Optimization of Clustering Distribution

inferred← citeshttps://doi.org/10.1007/978-981-97-5678-0_29openalex-snapshot

Dictionary Temporal Graph Network via Pre-training Embedding Distillation

inferred← citeshttps://doi.org/10.1007/978-981-97-5678-0_31openalex-snapshot

Variational Structural Deep Clustering Network

inferred← citeshttps://doi.org/10.1007/978-981-97-7679-5_9openalex-snapshot

Clustering with Adaptive Unsupervised Graph Convolution Network

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Community Detection Based on Enhancing Graph Autoencoder with Node Structural Role

inferred← citeshttps://doi.org/10.1007/978-981-99-2443-1_52openalex-snapshot

Community Detection Based on Graph Attention and Self-supervised Embedding

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Dual Deep Clustering

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Deep Structure and Attention Aware Subspace Clustering

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A novel clustering algorithm based on multi-layer features and graph attention networks

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Hierarchical attention network for attributed community detection of joint representation

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Dual-stream encoder neural networks with spectral constraint for clustering functional brain connectivity data

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ANGraph: attribute-interactive neighborhood-aggregative graph representation learning

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An integrated fuzzy neural supervision and attention-based graph neural network for improving network clustering

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DAC-HPP: deep attributed clustering with high-order proximity preserve

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Deep graph-level clustering using pseudo-label-guided mutual information maximization network

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Self-supervised graph clustering via attention auto-encoder with distribution specificity

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Contrastive graph clustering via enhanced hard sample mining and cluster-guiding

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DSGAC: deep self-supervised global attention for attributed graph clustering

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CG-MVC: structure-aware multi-view clustering with entropy-quantile curriculum learning

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Structure-guided attributed network embedding with “centroid” enhancement

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Semi-supervised graph convolutional deep embedded clustering

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Attribute graph clustering via dual-driven network with dynamic structure optimization and prototype contrast

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DiffGCC: diffusion-enhanced global–local graph contrastive clustering

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Graph relation embedding network for click-through rate prediction

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Spectral clustering with scale fairness constraints

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Contrastive prototype source-free adaptation boosted by inherent data structure

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A Comprehensive Survey on Subspace Clustering: Methods and Applications

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Deep convolutional self-paced clustering

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Boosting semi-supervised network representation learning with pseudo-multitasking

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Deep structural enhanced network for document clustering

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Graph contrastive learning with cross-encoder for community discovery

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Attribute community detection based on attribute edges weights fusion and graph embedding factorization

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Dynamic graph attention-guided graph clustering with entropy minimization self-supervision

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Deep graph clustering method with improved cluster structure feature learning

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Self-supervised deep clustering for spammer group detection

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Spatio-temporal unsupervised individual clustering for operating room videos

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Bipartite graph regularized robust low-rank matrix factorization for fast semi-supervised image clustering

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CPG-GCN: consensus-prototype guided graph convolutional network

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MvCConvFormer: The graph convolution transformer network with self-distillation for multi-view graph clustering

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scDEAN: a lightweight adaptive fusion model for clustering scRNA-seq data

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Inductive Subgraph Embedding for Link Prediction

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Deep Self-Supervised Attributed Graph Clustering for Social Network Analysis

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Multi-dimensional Topological Association Strengthening Clustering Network

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Local Community Detection Based on Core Nodes using Deep Feature Fusion

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Neighbor Contrast-based Multiple Self-supervised Incomplete Multi-view Clustering

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Joint learning of latent similarity and smooth features in attributed graph clustering

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Introducing the Cosine Clustering Index (CCI): A Balanced Approach to Evaluating Deep Clustering

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Constrained deep nonnegative matrix factorization with graph convolutional networks for unsupervised community detection

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Machine Learning in Bioinformatics

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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering

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Graph-to-cluster contrastive ratio variational graph autoencoder for deep graph clustering

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Deep multi-kernel cell clustering for single-cell RNA sequencing data

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scCAT: Single-cell Combined graph Attentional clustering for scRNA-seq analysis

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SCMS-Net: Self-Supervised Clustering-Based 3D Meshes Segmentation Network

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Similarity-smooth graph contrastive learning for community detection in adaptive oscillatory networks

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SCGC-JWAF: Shallow contrastive graph clustering with Jaccard-based weighted adaptive filtering

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Few-shot encrypted traffic classification via multi-task representation enhanced meta-learning

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Indirect estimation of pediatric reference interval via density graph deep embedded clustering

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A community detection model using node embedding approach and graph convolutional network with clustering technique

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MVMA-GCN: Multi-view multi-layer attention graph convolutional networks

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Progressive structure enhancement graph convolutional network for face clustering

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Contrastive deep graph clustering via higher-order heuristic augmentation and propagation

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Adaptive hypergraph clustering of trucks based on high-order mobility correlations

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Contrastive graph clustering with adaptive filter

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Mutual Boost Network for attributed graph clustering

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A graph-enhanced attention model for community detection in multiplex networks

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Community detection based on community perspective and graph convolutional network

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Attributed graph subspace clustering with residual compensation guided by adaptive dual manifold regularization

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AnoOnly: Semi-supervised anomaly detection with the only loss on anomalies

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CGCFS: A comparative graph clustering method based on feature and structural information

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High-order multi-view clustering for generic data

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Interest-driven community detection on attributed heterogeneous information networks

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Rethinking multi-level information fusion in temporal graphs: Pre-training then distilling for better embedding

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Incorporating attributes and multi-scale structures for heterogeneous graph contrastive learning

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Deep cut-informed graph embedding and clustering

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Neural generative model for clustering by separating particularity and commonality

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Adversarially regularized joint structured clustering network

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A two-stage deep graph clustering method for identifying the evolutionary patterns of the time series of animation view counts

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MHGC: Multi-scale hard sample mining for contrastive deep graph clustering

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Motif-based Contrastive Graph Clustering with clustering-oriented prompt

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Multi-scale graph contrastive learning for community detection in dynamic graphs

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An expert-knowledge-based algorithm for time-varying multi-objective coastal groundwater optimization

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Deep face clustering using residual graph convolutional network

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Deep linear graph attention model for attributed graph clustering

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Transformer-based Dynamic Fusion Clustering Network

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An efficient semi-supervised balanced cut with hard pairwise constraints and partial labels

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DCOM-GNN: A Deep Clustering Optimization Method for Graph Neural Networks

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Deep document clustering via adaptive hybrid representation learning

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Deep time-series clustering via latent representation alignment

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Attention-based Graph Clustering Network with Dual Information Interaction

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Disentangled hyperbolic representation learning for heterogeneous graphs

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Discovering personalized document partition via intention-aware deep document clustering

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A robust low-pass filtering graph diffusion clustering framework for hyperspectral images

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PGC-CSS: A parallel graph clustering framework with collaborative self-supervision

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SE-GSSL: Soft-Mask enhanced graph self-supervised learning with multi-aspect knowledge encoding and adaptive sample selection

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Cluster-guided and weight-decorrelated contrastive network for graph clustering

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SOM-GAT: Topological graph clustering via Self-Organizing Maps and Graph Attention Networks

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Contrastive graph clustering with a topology-sensitive noise augmentation framework

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Adaptive graph prompting for graph clustering

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Semi-supervised multi-level contrastive learning for deep clustering

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Graph Neural Networks: A bibliometrics overview

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Deep multi-view semi-supervised clustering with sample pairwise constraints

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Neighborhood contrastive representation learning for attributed graph clustering

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Deep Contrastive Clustering via Hard positive sample Debiased

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Self-supervised graph autoencoder with redundancy reduction for community detection

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An overview on deep clustering

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Meta-learning on dynamic node clustering knowledge graph for cold-start recommendation

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Adversarially deep interative-fused embedding clustering via joint self-supervised networks

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SCGC : Self-supervised contrastive graph clustering

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Towards multi-fusion graph neural network for single-cell RNA sequence clustering

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DASC: Learning discriminative latent space for video clustering

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Multi-view constraint disentangled GAT for recommendation

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stMHCG: High-confidence multi-view clustering for identification of spatial domains from spatially resolved transcriptomics

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BCDAN: A balanced method for community detection in attributed networks

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Consistency-Regularized Multi-Stage Joint-Perception Graph Fuzzy Clustering Algorithm

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Spectral embedding network for attributed graph clustering

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Attributed graph clustering with multi-task embedding learning

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Structure enhanced deep clustering network via a weighted neighbourhood auto-encoder

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Adaptive graph convolutional clustering network with optimal probabilistic graph

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Learning matrix factorization with scalable distance metric and regularizer

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Structure-aware deep clustering network based on contrastive learning

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Adaptive-weighted deep multi-view clustering with uniform scale representation

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T-distributed Stochastic Neighbor Network for unsupervised representation learning

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GSSCL: A framework for Graph Self-Supervised Curriculum Learning based on clustering label smoothing

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Graph clustering network with structure embedding enhanced

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Deep image clustering with contrastive learning and multi-scale graph convolutional networks

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Video anomaly detection guided by clustering learning

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Deep clustering via dual-supervised multi-kernel mapping

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Aggregation-aware MLP: An unsupervised approach for graph message-passing

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Three-way cluster-guided contrastive graph clustering

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stHGNN: Deciphering spatial transcriptomics data via dual hypergraph learning enhancement

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Dual Feature Enhancement Graph Clustering Network

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Explainable deep representation learning for clustering building-energy time series

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Deep learning-based prediction of in-hospital mortality for sepsis

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A deep multiple self-supervised clustering model based on autoencoder networks

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Prototype based contrastive graph clustering network for reducing false negatives

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Deep learning powered single-cell clustering framework with enhanced accuracy and stability

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Few-shot traffic classification based on autoencoder and deep graph convolutional networks

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CoLM 2 S: Contrastive self‐supervised learning on attributed multiplex graph network with multi‐scale information

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Multi‐graph convolutional clustering network

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A survey on deep learning based clustering methods and taxonomy for deep clustering

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MP-DEC: multi-perspective deep embedding custering for network protocol data

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Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network

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