Reference health
DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series
1 of 32 checkable references need attention · checked 2026-07-31
At the dated check, the references listed below either did not resolve in Crossref or DataCite, or carried a retraction notice. Each one is shown with the registry record that put it there.
28 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
References needing attention
does not resolve to a known work10.2307/1266761
The 31 checked references that resolve
resolves10.1109/ICMLA.2015.141
Evaluating Real-Time Anomaly Detection Algorithms -- The Numenta Anomaly Benchmark
resolves10.3390/app8091468
Unsupervised Novelty Detection Using Deep Autoencoders with Density Based Clustering
resolves10.1145/2783258.2788611
Generic and Scalable Framework for Automated Time-series Anomaly Detection
resolves10.1080/00401706.1983.10487848
Percentage Points for a Generalized ESD Many-Outlier Procedure
resolves10.1155/2016/9653230
An Improved ARIMA-Based Traffic Anomaly Detection Algorithm for Wireless Sensor Networks
resolves10.1016/j.eswa.2017.04.028
Detecting anomalies in time series data via a deep learning algorithm combining wavelets, neural networks and Hilbert transform
resolves10.1109/ACCESS.2018.2840086
Detecting Anomalies in Time Series Data via a Meta-Feature Based Approach
resolves10.1109/ICDM.2007.61
Disk Aware Discord Discovery: Finding Unusual Time Series in Terabyte Sized Datasets
resolves10.1145/347090.347160
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms
resolves10.1007/s10994-016-5567-7
Expected similarity estimation for large-scale batch and streaming anomaly detection
resolves10.1007/3-540-47887-6_53
Enhancing Effectiveness of Outlier Detections for Low Density Patterns
resolves10.1145/2500853.2500857
Enhancing one-class support vector machines for unsupervised anomaly detection
resolves10.1109/DSAA.2015.7344872
Anomaly detection in ECG time signals via deep long short-term memory networks
resolves10.1016/j.dss.2011.04.001
Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model
resolves10.1007/978-1-4471-0219-9_20
Applying LSTM to Time Series Predictable Through Time-Window Approaches
The 28 references without a DOI — listed, not checked
no DOI — not checkedref33
no DOI — not checkedDetection of anomalies in large scale accounting data using deep autoencoder networks
no DOI — not checkedTime series classification using multi-channels deep convolutional neural networks
no DOI — not checkedref37
no DOI — not checkedSTL: A seasonal-trend decomposition procedure based on loess
no DOI — not checkedAdversarial machine learning at scale
no DOI — not checkedAn introduction to outlier analysis
no DOI — not checkedRobust methods for unsupervised PCA-based anomaly detection
no DOI — not checkedA novel anomaly detection scheme based on principal component classifier
no DOI — not checkedref25
no DOI — not checkedref51
no DOI — not checkedNeural architecture search with reinforcement learning
no DOI — not checkedref58
no DOI — not checkedref54
no DOI — not checkedref53
no DOI — not checkedref10
no DOI — not checkedref40
no DOI — not checkedHistogram-based outlier score (HBOS): A fast unsupervised anomaly detection algorithm
no DOI — not checkedAnomaly detection in activities of daily living using one-class support vector machine
no DOI — not checkedref4
no DOI — not checkedAnomaly detection in large datasets
no DOI — not checkedLong short term memory networks for anomaly detection in time series
no DOI — not checkedref5
no DOI — not checkedref7
no DOI — not checkedDetecting anomalies in a time series database
no DOI — not checkedref45
no DOI — not checkedref48
no DOI — not checkedImageNet classification with deep convolutional neural networks
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