AI RESEARCH
NeuroRisk: Physics-Informed Neural Optimization for Risk-Aware Traffic Engineering
arXiv CS.LG
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ArXi:2605.12862v1 Announce Type: cross In production Wide-Area Networks (WANs), correlated failures dominate availability losses, forcing operators to reserve large safety margins that leave substantial capacity underutilized. Achieving high utilization under strict availability targets. therefore. requires risk-aware Traffic Engineering (TE) over dozens to hundreds of probabilistic failure scenarios-yet solving this problem at operational timescales remains elusive.