Results 41 to 50 of about 124,846 (268)
Deep learning technology of Internet of Things Blockchain in distribution network faults
Journal of Intelligent Systems, 2022 Nowadays, the development of human society and daily life are inseparable from the power supply. Therefore, people also put forward higher requirements for the reliability of distribution network, but power companies can only passively deal with ...
Zhang Hong, Li Rui, Shi Chuncheng
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Inversion of Bayesian networks
International Journal of Approximate ReasoningVariational autoencoders and Helmholtz machines use a recognition network (encoder) to approximate the posterior distribution of a generative model (decoder). In this paper we study the necessary and sufficient properties of a recognition network so that it can model the true posterior distribution exactly.
Jesse van Oostrum +2 more
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Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
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
Journal of Open Source SoftwareThe R package abn is a comprehensive tool for Bayesian Network (BN) analysis, a form of probabilistic graphical model. BNs are a type of statistical model that leverages the principles of Bayesian statistics and graph theory to provide a framework for representing complex multivariate data.
Delucchi, Matteo +3 more
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Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks [PDF]
Machine Learning, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nir Friedman, Daphne Koller
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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 +2 more
wiley +1 more source
Efficacy of Inebilizumab in N‐MOmentum Trial Participants With or Without Prior Immunosuppressants
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT This post hoc analysis examined the impact of prior immunosuppressants on the long‐term efficacy and safety of inebilizumab, a cluster of differentiation 19+ B‐cell–depleting monoclonal antibody, in participants with aquaporin‐4–seropositive neuromyelitis optica spectrum disorder from the N‐MOmentum trial (NTC02200770).
Bruce A. C. Cree +9 more
wiley +1 more source
Reliability Analysis of Vehicle Braking System Based on Hyperellipsoidal Dynamic Bayesian Network
Applied SciencesBrake 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
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Development of a smart system for gasoline car emissions diagnosis using Bayesian Network
Jurnal Ilmiah SINERGI, 2023 A vehicle exhaust emissions test is an activity carried out to determine the content of the remaining combustion products that occur in the fuel in the vehicle engine. Many people do not understand exhaust gas content from emission tests, so to make this
Dedik Romahadi +3 more
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