Six-month, CTEL-led programme blends machine learning, deep learning and generative AI with hands-on projects and a three-day ...
Abstract: This paper introduces a novel optimized hybrid model combining Long Short-Term Memory (LSTM) and Transformer deep learning architectures designed for power load forecasting. It leverages the ...
An ML-powered monitoring system that detects anomalous BGP route behavior in real-time. The system processes live BGP update streams, applies multiple detectors (Isolation Forest + LSTM autoencoder), ...
Abstract: The prevalence of zero values in zero-inflated time-series (ZI-TS) data poses significant challenges for traditional LSTM networks in learning long-term dependencies and trends. Specifically ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results