A Bayesian framework learns uncertainties from data to generate robust multi-topology express network designs that reduce tail delivery risks at modest extra cost in simulations.
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A tutorial framing deep learning as a complement to optimization for sequential decision-making under uncertainty, with applications in supply chains, healthcare, and energy.
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Bayesian Multi-Topology Express Transportation Network Design under Posterior Predictive Demand, Sorting-Efficiency and Delivery-Time Uncertainty
A Bayesian framework learns uncertainties from data to generate robust multi-topology express network designs that reduce tail delivery risks at modest extra cost in simulations.
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Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
A tutorial framing deep learning as a complement to optimization for sequential decision-making under uncertainty, with applications in supply chains, healthcare, and energy.