Results 11 to 20 of about 19,576 (91)
Deterministic, quenched, and annealed parameter estimation for heterogeneous network models. [PDF]
Physical Review E, 2023 At least two different approaches to define and solve statistical models for the analysis of economic systems exist: the typical, econometric one, interpreting the gravity model specification as the expected link weight of an arbitrary probability ...
M. Di Vece +2 more
semanticscholar +1 more source
Analysis, Prediction, and Control of Epidemics: A Survey from Scalar to Dynamic Network Models [PDF]
IEEE Circuits and Systems Magazine, 2021 During the ongoing COVID-19 pandemic, mathematical models of epidemic spreading have emerged as powerful tools to produce valuable predictions of the evolution of the pandemic, helping public health authorities decide which intervention policies should ...
Lorenzo Zino, M. Cao
semanticscholar +1 more source
A comparative study of convolutional neural network models for wind field downscaling [PDF]
Meteorological Applications, 2020 We analyze the applicability of convolutional neural network (CNN) architectures for downscaling of short‐range forecasts of near‐surface winds on extended spatial domains.
Kevin Höhlein +3 more
semanticscholar +1 more source
Sustainability, 2022 The paper firstly proposes a deterministic deep feedforward neural network model aimed at predicting the city bus velocity profile over receding time horizon based on the following inputs: actual vehicle position, actual velocity or short-term history of
Jakov Topić, B. Škugor, J. Deur
semanticscholar +1 more source
Applied Sciences, 2022 Hyperparameter tuning is a critical function necessary for the effective deployment of most machine learning (ML) algorithms. It is used to find the optimal hyperparameter settings of an ML algorithm in order to improve its overall output performance. To
Ismail Damilola Raji +5 more
semanticscholar +1 more source
Deterministic and probabilistic deep learning models for inverse design of broadband acoustic cloak [PDF]
Physical Review Research, 2020 Concealing an object from incoming waves (light and/or sound) remained science fiction for a long time due to the absence of wave-shielding materials in nature.
W. Ahmed +3 more
semanticscholar +1 more source
IEEE Transactions on Antennas and Propagation, 2022 Billions of mobile terminals will be deployed in various Internet of Things (IoT), in which millimeter-wave (mmWave) technology will be gradually applied.
Xiongwen Zhao +8 more
semanticscholar +1 more source
A comparison of Monte Carlo sampling methods for metabolic network models
PLoS ONE, 2020 Reaction rates (fluxes) in a metabolic network can be analyzed using constraint-based modeling which imposes a steady state assumption on the system. In a deterministic formulation of the problem the steady state assumption has to be fulfilled exactly ...
Shirin Fallahi, H. Skaug, G. Alendal
semanticscholar +1 more source
Beyond Tree Embeddings – a Deterministic Framework for Network Design with Deadlines or Delay [PDF]
IEEE Annual Symposium on Foundations of Computer Science, 2020 We consider network design problems with deadline or delay. All previous results for these models are based on randomized embedding of the graph into a tree (HST) and then solving the problem on this tree. We show that this is not necessary.
Y. Azar, Noam Touitou
semanticscholar +1 more source
Control of interbank contagion under partial information [PDF]
, 2014 International audienceWe consider a stylized core-periphery financial network in which links lead to the creation of projects in the outside economy but make banks prone to contagion risk.
Amini, Hamed +2 more
core +5 more sources