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Fast uncertainty quantification for dynamic flux balance analysis using non-smooth polynomial chaos expansions
JA Paulson, M Martin-Casas… - PLoS computational …, 2019 - journals.plos.org
We present a novel surrogate modeling method that can be used to accelerate the solution
of uncertainty quantification (UQ) problems arising in nonlinear and non-smooth models of …
of uncertainty quantification (UQ) problems arising in nonlinear and non-smooth models of …
Multi-target state extraction for the SMC-PHD filter
W Si, L Wang, Z Qu - Sensors, 2016 - mdpi.com
The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been
demonstrated to be a favorable method for multi-target tracking. However, the time-varying …
demonstrated to be a favorable method for multi-target tracking. However, the time-varying …
Local cliques in ER-perturbed random geometric graphs
Random graphs are mathematical models that have applications in a wide range of
domains. We study the following model where one adds Erd\H {o} s--R\'enyi (ER) type …
domains. We study the following model where one adds Erd\H {o} s--R\'enyi (ER) type …
[BOOK][B] Unravel the Geometry and Topology behind Noisy Networks
M Tian - 2020 - search.proquest.com
Graphs and network data are ubiquitous across a wide spectrum of scientific and application
domains. Often in practice, an input graph can be considered as an observed snapshot of a …
domains. Often in practice, an input graph can be considered as an observed snapshot of a …
[CITATION][C] On the clique number of noisy random geometric graphs
[CITATION][C] PROF. DR. GARETH W. PETERS
GW Peters, TS Books - 2004 - University of California Santa …