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Tractable Learning and Inference for Large-Scale Probabilistic Boolean Networks

机译:大规模概率布尔网络的可学习和推理

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摘要

Probabilistic Boolean networks (PBNs) have previously been proposed so as to gain insights into complex dynamical systems. However, identification of large networks and their underlying discrete Markov chain which describes their temporal evolution still
机译:先前已经提出了概率布尔网络(PBN),以便深入了解复杂的动力学系统。然而,大型网络及其底层离散马尔可夫链的识别仍然描述了它们的时间演化。

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