Bayonet: probabilistic inference for networks
Timon Gehr, Saša Misailovíc, Petar Tsankov, Laurent Vanbever, Pascal Wiesmann, Martin Vechev · 2018
Network operators often need to ensure that important probabilistic properties are met, such as that the probability of network congestion is below a certain threshold. Ensuring such properties is challenging and requires both a suitable language for probabilistic networks and an automated procedure for answering probabilistic inference queries.