Deep Learning framework for large-scale network traffic forecasting on the CESNET-TimeSeries24 dataset.
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Jun 18, 2026 - Jupyter Notebook
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cesnet-timeseries24
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Anomaly detection project utilizing CESNET-TimeSeries24 real-world network traffic data. Employs n_flows for comprehensive EDA, SARIMAX modeling, and LSTM-based forecasting to identify anomalous network behaviors. Focuses on time series analysis for robust detection
data-science machine-learning ai deep-learning time-series signal-processing ml intrusion-detection research-project network-analysis unsupervised-learning cesnet cyber-security network-traffic statistical-models network-security anomaly-detection real-world-data timeseries-analysis cesnet-timeseries24
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Dec 31, 2025 - Jupyter Notebook
Decision-aware traffic forecasting for backbone capacity planning. Asymmetric losses and conformal calibration to minimize operator cost rather than RMSE. Evaluated on Abilene, GÉANT, and CESNET-TimeSeries24 with 20-seed paired-bootstrap CIs.
capacity-planning service-level-agreement pytorch lstm network-management quantile-regression time-series-forecasting conformal-prediction backbone-networks traffic-forecasting asymmetric-loss network-traffic-prediction decision-focused-learning cesnet-timeseries24 abilene-dataset geant-dataset
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Jun 29, 2026 - Python
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