geant-dataset

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SuryanshSS1011 / match-loss-to-cost

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

Updated Jun 29, 2026
Python

mahins32 / HaiFormer-6G

Star

Hierarchical AI-Native Transformer–GNN Framework for Autonomous 6G Network Management using the GÉANT Dataset

uncertainty-estimation multi-task-learning explainable-ai digital-twin graph-neural-networks zero-touch-network 6g-networks geant-dataset spatio-temporal-transformer

Updated Jun 27, 2026
Jupyter Notebook

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