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Deep Dual Support Vector Data description for anomaly detection on attributed networks

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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-030-01258-8_44openalex-snapshot

Highly-Economized Multi-view Binary Compression for Scalable Image Clustering

inferredcites →https://doi.org/10.1007/978-3-030-47436-2_52openalex-snapshot

Correlation-Aware Deep Generative Model for Unsupervised Anomaly Detection

inferredcites →https://doi.org/10.1023/b:mach.0000008084.60811.49openalex-snapshot

Support Vector Data Description

inferredcites →https://doi.org/10.1109/cvpr.2019.00301openalex-snapshot

OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations

inferredcites →https://doi.org/10.1109/icassp40776.2020.9053387openalex-snapshot

Anomalydae: Dual Autoencoder for Anomaly Detection on Attributed Networks

inferredcites →https://doi.org/10.1109/icdm.2006.165openalex-snapshot

Using an Ensemble of One-Class SVM Classifiers to Harden Payload-based Anomaly Detection Systems

inferredcites →https://doi.org/10.1109/icdm.2013.88openalex-snapshot

Statistical Selection of Congruent Subspaces for Mining Attributed Graphs

inferredcites →https://doi.org/10.1109/icdm.2016.0072openalex-snapshot

Homophily, Structure, and Content Augmented Network Representation Learning

inferredcites →https://doi.org/10.1109/icdm.2018.00071openalex-snapshot

A United Approach to Learning Sparse Attributed Network Embedding

inferredcites →https://doi.org/10.1109/icdm.2018.8626170openalex-snapshot

Binarized attributed network embedding

inferredcites →https://doi.org/10.1109/infcom.2012.6195548openalex-snapshot

Robust feature selection and robust PCA for internet traffic anomaly detection

inferredcites →https://doi.org/10.1109/tits.2019.2950416openalex-snapshot

Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting

inferredcites →https://doi.org/10.1109/tkde.2018.2819980openalex-snapshot

Attributed Social Network Embedding

inferredcites →https://doi.org/10.1109/tkde.2018.2833443openalex-snapshot

Heterogeneous Information Network Embedding for Recommendation

inferredcites →https://doi.org/10.1109/tkde.2018.2849727openalex-snapshot

A Survey on Network Embedding

inferredcites →https://doi.org/10.1109/tnnls.2020.3018790openalex-snapshot

Inductive Structure Consistent Hashing via Flexible Semantic Calibration

inferredcites →https://doi.org/10.1109/tpami.2018.2847335openalex-snapshot

Binary Multi-View Clustering

inferredcites →https://doi.org/10.1109/tpami.2021.3059313openalex-snapshot

Heterogeneous Hypergraph Variational Autoencoder for Link Prediction

inferredcites →https://doi.org/10.1137/1.9781611974348.24openalex-snapshot

Scalable Anomaly Ranking of Attributed Neighborhoods

inferredcites →https://doi.org/10.1137/1.9781611974973.71openalex-snapshot

Accelerated Attributed Network Embedding

inferredcites →https://doi.org/10.1137/1.9781611975673.67openalex-snapshot

Deep Anomaly Detection on Attributed Networks

inferredcites →https://doi.org/10.1145/1541880.1541882openalex-snapshot

Anomaly detection

inferredcites →https://doi.org/10.1145/2339530.2339670openalex-snapshot

Intrusion as (anti)social communication

inferredcites →https://doi.org/10.1145/2500853.2500857openalex-snapshot

Enhancing one-class support vector machines for unsupervised anomaly detection

inferredcites →https://doi.org/10.1145/2623330.2623682openalex-snapshot

Focused clustering and outlier detection in large attributed graphs

inferredcites →https://doi.org/10.1145/2623330.2623732openalex-snapshot

DeepWalk

inferredcites →https://doi.org/10.1145/2783258.2783296openalex-snapshot

Heterogeneous Network Embedding via Deep Architectures

inferredcites →https://doi.org/10.1145/2783258.2788606openalex-snapshot

Collective Spammer Detection in Evolving Multi-Relational Social Networks

inferredcites →https://doi.org/10.1145/2939672.2939765openalex-snapshot

Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations

inferredcites →https://doi.org/10.1145/3018661.3018667openalex-snapshot

Label Informed Attributed Network Embedding

inferredcites →https://doi.org/10.1145/3097983.3098052openalex-snapshot

Anomaly Detection with Robust Deep Autoencoders

inferredcites →https://doi.org/10.1145/3139241openalex-snapshot

Discovering Communities and Anomalies in Attributed Graphs

inferredcites →https://doi.org/10.1145/3269206.3272010openalex-snapshot

Heterogeneous Graph Neural Networks for Malicious Account Detection

inferredcites →https://doi.org/10.1145/3357384.3358074openalex-snapshot

SpecAE

inferredcites →https://doi.org/10.1145/3377850openalex-snapshot

Jointly Learning Representations of Nodes and Attributes for Attributed Networks

inferredcites →https://doi.org/10.1162/089976601750264965openalex-snapshot

Estimating the Support of a High-Dimensional Distribution

inferredcites →https://doi.org/10.1184/r1/6475745openalex-snapshot

Group Anomaly Detection using Flexible Genre Models

inferredcites →https://doi.org/10.1198/tech.2003.s783openalex-snapshot

Principal Component Analysis

inferredcites →https://doi.org/10.1609/aaai.v33i01.330112openalex-snapshot

Outlier Aware Network Embedding for Attributed Networks

inferredcites →https://doi.org/10.24963/ijcai.2017/299openalex-snapshot

Radar: Residual Analysis for Anomaly Detection in Attributed Networks

inferredcites →https://doi.org/10.24963/ijcai.2018/488openalex-snapshot

ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks

inferredcites →https://doi.org/10.48550/arxiv.1605.07717openalex-snapshot

Deep Structured Energy Based Models for Anomaly Detection

inferredcites →https://doi.org/10.48550/arxiv.1706.02216openalex-snapshot

Inductive Representation Learning on Large Graphs

What points at this work

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

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Statistically inspired discrepancy detection for anomalous spatio-temporal graphs

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A robust framework for topology-based anomaly detection in attributed networks using graph attention networks, substructure analysis, and data augmentation

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Anomaly detection in graph databases using graph neural networks: Identifying unusual patterns in graphs

inferred← citeshttps://doi.org/10.1016/j.eswa.2024.123535openalex-snapshot

Exploiting negative correlation for unsupervised anomaly detection in contaminated time series

inferred← citeshttps://doi.org/10.1016/j.ijcce.2022.08.002openalex-snapshot

An unsupervised deep learning ensemble model for anomaly detection in static attributed social networks

inferred← citeshttps://doi.org/10.1016/j.ins.2023.119840openalex-snapshot

Deep joint adversarial learning for anomaly detection on attribute networks

inferred← citeshttps://doi.org/10.1016/j.ins.2024.120520openalex-snapshot

DualGAD: Dual-bootstrapped self-supervised learning for graph anomaly detection

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ANOGAT-Sparse-TL: A hybrid framework combining sparsification and graph attention for anomaly detection in attributed networks using the optimized loss function incorporating the Twersky loss for improved robustness

inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114268openalex-snapshot

Diffusion-based anomaly representation enhancement on graphs

inferred← citeshttps://doi.org/10.1016/j.neucom.2024.128379openalex-snapshot

CGAD: A novel contrastive learning-based framework for anomaly detection in attributed networks

inferred← citeshttps://doi.org/10.1016/j.patcog.2026.114234openalex-snapshot

Improved Graph Anomaly Detection through global information

inferred← citeshttps://doi.org/10.1016/j.patrec.2024.05.004openalex-snapshot

Adversarial regularized attributed network embedding for graph anomaly detection

inferred← citeshttps://doi.org/10.1016/j.ymssp.2024.111489openalex-snapshot

M-band wavelet network for machine anomaly detection from a frequency perspective

inferred← citeshttps://doi.org/10.1038/s41598-024-51374-3openalex-snapshot

Graph autoencoder with mirror temporal convolutional networks for traffic anomaly detection

inferred← citeshttps://doi.org/10.1038/s41598-025-19650-yopenalex-snapshot

Unified representation and scoring framework for anomaly detection in attributed networks with emphasis on structural consistency and attribute integrity

inferred← citeshttps://doi.org/10.1038/s41598-025-28842-5openalex-snapshot

One-class edge classification through heterogeneous hypergraph for causal discovery

inferred← citeshttps://doi.org/10.1063/5.0329086openalex-snapshot

Attention-enhanced substructure detection for topology-based node anomalies in attributed networks

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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks

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A Deep Learning Approach Using Graph Neural Networks for Anomaly Detection in Air Quality Data Considering Spatiotemporal Correlations

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Graph Anomaly Detection With Graph Neural Networks: Current Status and Challenges

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Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques

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STEAM: SVDD-based Anomaly Detection on Attributed Networks via Multi-Autoencoders

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Attribute Network Anomaly Detection Based on Canonical Correlation Analysis Using Deep Adversarial Learning

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Trans-DAE: Transformer-based Double Autoencoder for Anomaly Detection on Attributed Networks

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An Attributed Network Anomaly Detection Method Based on Dual Autoencoder Joint Embedding

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Unsupervised Anomaly Detection on Attributed Networks With Graph Contrastive Learning for Consumer Electronics Security

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NMFAD: Neighbor-Aware Mask-Filling Attributed Network Anomaly Detection

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CaCo: Attributed Network Anomaly Detection via Canonical Correlation Analysis

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Context Correlation Discrepancy Analysis for Graph Anomaly Detection

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DuDi: Dual-Scope Discrepancy-Aware Attributed Network Anomaly Detection

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Mixed Metric Learning with Distribution Alignment for Attributed Network Anomaly Detection

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Anomaly detection in multi-tiered cellular networks using LSTM and 1D CNN

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An adversarial variational graph autoencoder with contrastive learning for robust anomaly detection in large scale attributed networks

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Detecting anomalies in graph networks on digital markets

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Ct-Fagl: Continuous-Time Frequency-Attentive Graph Learning for Dynamic Fraud Detection in Financial Networks

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