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DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction. [PDF]
Sci RepGulMohamed RB +3 more
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Optimal Operation of Integrated Multi-Energy Systems Under Uncertainty, 2022
Qiuwei Wu +4 more
semanticscholar +2 more sources
Qiuwei Wu +4 more
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Geometric Anchor Correspondence Mining with Uncertainty Modeling for Universal Domain Adaptation
Computer Vision and Pattern Recognition, 2022Universal domain adaptation (UniDA) aims to transfer the knowledge learned from a label-rich source domain to a label-scarce target domain without any constraints on the label space.
Liang Chen +4 more
semanticscholar +1 more source
Decision-Dependent Uncertainty Modeling in Power System Operational Reliability Evaluations
IEEE Transactions on Power Systems, 2021The integration of the variable renewable energies makes the operation conditions of the power system ever-changeable. Consequently, the power system operational reliability evaluation is increasingly important.
Bo Hu +6 more
semanticscholar +1 more source
Model Uncertainty, State Uncertainty, and State-Space Models [PDF]
SSRN Electronic Journal, 2012 State-space models have been increasingly used to study macroeconomic and financial problems. A state-space representation consists of two equations, a measurement equation which links the observed variables to unobserved state variables and a transition equation describing the dynamics of the state variables.
Young, ER, Luo, Y, Nie, J
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Journal of the European Economic Association, 2015
We study decision problems in which consequences of the various alternative actions depend on states determined by a generative mechanism representing some natural or social phenomenon. Model uncertainty arises because decision makers may not know this mechanism. Two types of uncertainty result, a state uncertainty within models and a model uncertainty
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We study decision problems in which consequences of the various alternative actions depend on states determined by a generative mechanism representing some natural or social phenomenon. Model uncertainty arises because decision makers may not know this mechanism. Two types of uncertainty result, a state uncertainty within models and a model uncertainty
+6 more sources
Orthogonal Uncertainty Modeling in the Engineering of Cyber-Physical Systems
IEEE Transactions on Automation Science and Engineering, 2020Software-intensive cyber-physical systems (CPS) perform essential tasks such as controlling automated production processes in industrial production plants.
Torsten Bandyszak +5 more
semanticscholar +1 more source