Abstract: Anomaly detection in multivariate time series has gained significant attention in past few years. The rarity of anomalies, considerable data volatility, absence of anomaly labels, and need ...

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├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...

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ABSTRACT: Time series anomaly detection is important in fields such as industrial control, but faces challenges such as data distribution drifting over time, diverse normal patterns, and training data ...

1 Analytics Department, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India 2 Department of Data Science, School of Computer Science and Engineering ...

Time series anomaly detection is important in fields such as industrial control, but faces challenges such as data distribution drifting over time, diverse normal patterns, and training data ...