Results 51 to 60 of about 235,639 (329)
Benchmarking dynamic Bayesian network structure learning algorithms [PDF]
2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO), 2013 Dynamic Bayesian Networks (DBNs) are probabilistic graphical models dedicated to modeling multivariate time series. Two-time slice BNs (2-TBNs) are the most current type of these models. Static BN structure learning is a well-studied domain. Many approaches have been proposed and the quality of these algorithms has been studied over a range of di erent
Trabelsi, Ghada +3 more
openaire +3 more sources
Energy financial risk early warning model based on Bayesian network
Energy Reports, 2023 Oil is a global, non-renewable energy source, which plays a pivotal role in the development of the global economy and the strategic reserve system. With the expansion of crude oil futures trading scale, crude oil is no longer a pure energy commodity, but
Lin Wei, Hanyue Yu, Bin Li
doaj +1 more source
Sensorimotor coupling via Dynamic Bayesian Networks
2008 IEEE International Conference on Robotics and Automation, 2008 In this paper we consider the problem of sensorimotor coordination in a Bayesian framework. To this end we introduce a novel kind of Dynamic Bayesian Network serving as the core tool to integrate active vision and task-constrained motor behaviors. The proposed system is put into work by addressing the challenging task of realistic drawing performed by ...
R. Coen Cagli +4 more
openaire +3 more sources
Dynamic Bayesian networks for integrated neural computation [PDF]
First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings., 2004 Understanding the clinical outcomes of brain lesions necessitates knowing how networks of cerebral structures implement cognitive or sensorimotor functions. Functional neuroimaging techniques provide useful insights on what the networks are, and when and how much they activate.
Labatut, Vincent, Pastor, Josette
openaire +2 more sources
FEBS Open Bio, EarlyView.Evolutionary analysis across 32 placental mammals identified positive selection at residues H148 and W149 in the immune receptor FcγR1. Ancestral reconstruction combined with molecular dynamics simulations reveals how these mutations may influence receptor structure and dynamics, providing insight into the evolution of antibody recognition and immune ...
David A. Young +7 more
wiley +1 more source
Dynamic Railway Derailment Risk Analysis with Text-Data-Based Bayesian Network
Applied Sciences, 2021 In recent years, transportation system safety analysis has become increasingly challenging and highly demanding. Unstructured data contain sufficient information from which inherent interactions can be extracted.
Liu Yang +3 more
doaj +1 more source
Bayesian inference for dynamic social network data [PDF]
Journal of Statistical Planning and Inference, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Koskinen, Johan H., Snijders, Tom A B
openaire +3 more sources
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 +3 more
wiley +1 more source
, 2016 We discuss Bayesian forecasting of increasingly high-dimensional time series, a key area of application of stochastic dynamic models in the financial industry and allied areas of business.
West, Mike, Xie, Meng, Zhao, Zoey Yi
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 +4 more
wiley +1 more source