:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Jo, Hayoung, Lee, Seong-Whan
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2401.13872
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels
by: Dong, Xiangyu, et al.
Published: (2025)

Multi-Context Temporal Consistent Modeling for Referring Video Object Segmentation
by: Choi, Sun-Hyuk, et al.
Published: (2025)

Unsupervised Anomaly Prediction with N-BEATS and Graph Neural Network in Multi-variate Semiconductor Process Time Series
by: Sorensen, Daniel, et al.
Published: (2025)

Improving Graph Neural Networks by Learning Continuous Edge Directions
by: Pahng, Seong Ho, et al.
Published: (2024)

Prospective Multi-Graph Cohesion for Multivariate Time Series Anomaly Detection
by: Chen, Jiazhen, et al.
Published: (2025)

Optimized Weight Initialization on the Stiefel Manifold for Deep ReLU Neural Networks
by: Lee, Hyungu, et al.
Published: (2025)

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection
by: Jin, Ming, et al.
Published: (2023)

When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
by: Park, Min-Yeong, et al.
Published: (2025)

Three Revisits to Node-Level Graph Anomaly Detection: Outliers, Message Passing and Hyperbolic Neural Networks
by: Gu, Jing, et al.
Published: (2024)

Calibration-Free EEG-based Driver Drowsiness Detection with Online Test-Time Adaptation
by: Jang, Geun-Deok, et al.
Published: (2025)

Graph Anomaly Detection in Time Series: A Survey
by: Ho, Thi Kieu Khanh, et al.
Published: (2023)

Robust Weight Initialization for Tanh Neural Networks with Fixed Point Analysis
by: Lee, Hyunwoo, et al.
Published: (2024)

Impact of Recurrent Neural Networks and Deep Learning Frameworks on Real-time Lightweight Time Series Anomaly Detection
by: Lee, Ming-Chang, et al.
Published: (2024)

GraphSubDetector: Time Series Subsequence Anomaly Detection via Density-Aware Adaptive Graph Neural Network
by: Chen, Weiqi, et al.
Published: (2024)

Contaminated Multivariate Time-Series Anomaly Detection with Spatio-Temporal Graph Conditional Diffusion Models
by: Ho, Thi Kieu Khanh, et al.
Published: (2023)

Capsule Neural Networks as Noise Stabilizer for Time Series Data
by: Kim, Soyeon, et al.
Published: (2024)

Continuous Wavelet Transform and Siamese Network-Based Anomaly Detection in Multi-variate Semiconductor Process Time Series
by: Dey, Bappaditya, et al.
Published: (2025)

ENADPool: The Edge-Node Attention-based Differentiable Pooling for Graph Neural Networks
by: Zhao, Zhehan, et al.
Published: (2024)

Temporal-Conditioned Normalizing Flows for Multivariate Time Series Anomaly Detection
by: Baumgartner, David, et al.
Published: (2026)

Node-Time Conditional Prompt Learning In Dynamic Graphs
by: Yu, Xingtong, et al.
Published: (2024)

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model
by: Ju, Yeong-Joon, et al.
Published: (2025)

TransNAS-TSAD: Harnessing Transformers for Multi-Objective Neural Architecture Search in Time Series Anomaly Detection
by: Haq, Ijaz Ul, et al.
Published: (2023)

Node-level Contrastive Unlearning on Graph Neural Networks
by: Lee, Hong kyu, et al.
Published: (2025)

DEGNN: Dual Experts Graph Neural Network Handling Both Edge and Node Feature Noise
by: Hasegawa, Tai, et al.
Published: (2024)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)

Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection
by: Bei, Yuanchen, et al.
Published: (2024)

Multivariate Time-Series Anomaly Detection based on Enhancing Graph Attention Networks with Topological Analysis
by: Liu, Zhe, et al.
Published: (2024)

Temporal Graph Networks for Graph Anomaly Detection in Financial Networks
by: Kim, Yejin, et al.
Published: (2024)

Anomaly Detection for Non-stationary Time Series using Recurrent Wavelet Probabilistic Neural Network
by: Yang, Pu, et al.
Published: (2025)

KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks
by: Zhou, Quan, et al.
Published: (2024)

Robust Group Anomaly Detection for Quasi-Periodic Network Time Series
by: Yang, Kai, et al.
Published: (2025)

Robust Anomaly Detection with Graph Neural Networks using Controllability
by: Wei, Yifan, et al.
Published: (2025)

PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
by: Lee, Sang-Hoon, et al.
Published: (2024)

Harnessing Contrastive Learning and Neural Transformation for Time Series Anomaly Detection
by: Chen, Katrina, et al.
Published: (2023)

Contrast to Detect: Dynamic Graph Contrastive Regularization for Unsupervised Anomaly Detection in Multivariate Time Series
by: Pei, Yunhua, et al.
Published: (2026)

CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting
by: Koumar, Josef, et al.
Published: (2024)

Adaptive-GraphSketch: Real-Time Edge Anomaly Detection via Multi-Layer Tensor Sketching and Temporal Decay
by: Ekle, Ocheme Anthony, et al.
Published: (2025)

Explainable Time Series Anomaly Detection using Masked Latent Generative Modeling
by: Lee, Daesoo, et al.
Published: (2023)

Explaining Graph Neural Networks for Node Similarity on Graphs
by: Daza, Daniel, et al.
Published: (2024)

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
by: Dong, Xiangyu, et al.
Published: (2023)