Results 61 to 70 of about 39,041 (304)

Bayesian dynamic modeling and monitoring of network flows [PDF]

Network Science, 2019
AbstractIn the context of a motivating study of dynamic network flow data on a large-scale e-commerce website, we develop Bayesian models for online/sequential analysis for monitoring and adapting to changes reflected in node–node traffic. For large-scale networks, we customize core Bayesian time series analysis methods using dynamic generalized linear
Xi Chen 0049, David Banks, Mike West
openaire   +2 more sources

The fidelity of dynamic signaling by noisy biomolecular networks [PDF]

, 2013
Cells live in changing, dynamic environments. To understand cellular decision-making, we must therefore understand how fluctuating inputs are processed by noisy biomolecular networks.
Voliotis Margaritis, Margaritis Voliotis, Margaritis Voliotis (395876), Bowsher, CG, Bowsher Clive G., Peter S Swain, Swain, Peter S, Clive G Bowsher, Peter S. Swain, Bowsher, Clive G., Voliotis, Margaritis, Clive G. Bowsher (395875), Bowsher, Clive G, Clive G. Bowsher, Peter S. Swain (238162), Voliotis, M, Swain, Peter S., Swain, PS, Swain Peter S.   +18 more
core   +1 more source

Directed evolution of enzymes at the crossroads of tradition and innovation

FEBS Open Bio, EarlyView.
An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova, Andrej Mirossay, Erik Sedlak   +2 more
wiley   +1 more source

Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones

Advanced Engineering Materials, EarlyView.
A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Reliability Analysis of Vehicle Braking System Based on Hyperellipsoidal Dynamic Bayesian Network

Applied Sciences
Brake systems are subjected to various factors such as wear and fatigue over a long period of time. They bring a great challenge to the reliability analysis of the braking system.
Yingjie Tian, Jing Wen, Shubin Zheng
doaj   +1 more source

Bayesian topology identification of linear dynamic networks

, 2019
In networks of dynamic systems, one challenge is to identify the interconnection structure on the basis of measured signals. Inspired by a Bayesian approach in [1], in this paper, we explore a Bayesian model selection method for identifying the ...
Control Systems, Bottegal, Giulio, Shi, Shengling, Dynamic Networks: Data-Driven Modeling and Control, Van den Hof, Paul M.J.; id_orcid   +4 more
core   +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang, Santiago Benito, Özge Özgün, Sebastian Weber, Markus Stricker   +4 more
wiley   +1 more source

CausNet-partial: 'Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints.

PLoS ONE
In our recent work, we developed a novel dynamic programming algorithm to find optimal Bayesian networks with parent set constraints. This 'generational orderings' based dynamic programming algorithm-CausNet-efficiently searches the space of possible ...
Nand Sharma, Joshua Millstein
doaj   +1 more source

System-of-Systems Resilience Analysis and Design Using Bayesian and Dynamic Bayesian Networks

Mathematics
A System-of-Systems (SoS) is characterized both by independence and by inter-dependency. This inter-dependency, while allowing an SoS to achieve its objectives, also means that failures can cascade throughout the SoS. An SoS needs to be resilient to deal
Tianci Jiao, Hao Yuan, Jing Wang, Jun Ma, Xiaoling Li, Aimin Luo   +5 more
doaj   +1 more source

Dependency Parsing with Dynamic Bayesian Network

CoRR, 2007
6 ...
Virginia Savova, Leonid Peshkin
openaire   +3 more sources