Results 81 to 90 of about 6,917,983 (390)
Free energy of Bayesian Convolutional Neural Network with Skip Connection [PDF]
arXiv, 2023 Since the success of Residual Network(ResNet), many of architectures of Convolutional Neural Networks(CNNs) have adopted skip connection. While the generalization performance of CNN with skip connection has been explained within the framework of Ensemble Learning, the dependency on the number of parameters have not been revealed. In this paper, we show
arxiv
A practical Bayesian framework for backpropagation networks [PDF]
, 1992 A quantitative and practical Bayesian framework is described for learning of mappings in feedforward networks. The framework makes possible (1) objective comparisons between solutions using alternative network architectures, (2) objective stopping rules ...
MacKay, David J. C.
core
Advanced Materials, EarlyView.Reversible protonic ceramic electrochemical cells (R‐PCECs) face challenges from sluggish and unstable oxygen reduction and evolution reactions in the air electrode. This review discusses recent progress in triple‐conducting air electrodes, emphasizing mechanisms, performance factors, and design strategies, offering guidance for creating efficient and ...
Xi Chen +8 more
wiley +1 more source
High-Dimensional Bayesian Network Inference From Systems Genetics Data Using Genetic Node Ordering
Frontiers in Genetics, 2019 Studying the impact of genetic variation on gene regulatory networks is essential to understand the biological mechanisms by which genetic variation causes variation in phenotypes. Bayesian networks provide an elegant statistical approach for multi-trait
Lingfei Wang +6 more
doaj +1 more source
Smart Dust for Chemical Mapping
Advanced Materials, EarlyView.This review article explores the advancement of smart dust networks for high‐resolution spatial and temporal chemical mapping. Comprising miniature, wireless sensors, and communication devices, smart dust autonomously collects, processes, and transmits data via swarm‐based communication.
Indrajit Mondal, Hossam Haick
wiley +1 more source
A Bayesian Network Approach to Causation Analysis of Road Accidents Using Netica
, 2017 Based on an overall consideration of factors affecting road safety evaluations, the Bayesian network theory based on probability risk analysis was applied to the causation analysis of road accidents.
Xin Zou, W. Yue
semanticscholar +1 more source
Pair-Copula Bayesian Networks [PDF]
Journal of Computational and Graphical Statistics, 2016 Pair-copula Bayesian networks (PCBNs) are a novel class of multivariate statistical models, which combine the distributional flexibility of pair-copula constructions (PCCs) with the parsimony of conditional independence models associated with directed acyclic graphs (DAGs).
Alexander Bauer, Claudia Czado
openaire +3 more sources
Research on the Evolution of Defects Initiation and the Diffusion of Dopant on the Si/SiO2 Interface
Advanced Materials Interfaces, EarlyView.This review mainly introduces the recent investigations on the mechanisms of interface defect initiation and dopant diffusion, and the comparisons and discussions of the initial mechanism of defects, structures of defects to provide valuable guidance for improving the performance and extending the lifespan of Si/SiO2 interfaces.
Yunqi Yang +7 more
wiley +1 more source
Advanced Optical Materials, EarlyView.Photochromic compounds are versatile ingredients for the development of Chemical AI. When they are embedded in a tight microenvironment, they become Markov blankets. They are also valuable for processing Boolean and Fuzzy logic. They contribute to neuromorphic engineering in wetware based on opto‐chemical signals exchanged with oscillatory chemical ...
Pier Luigi Gentili
wiley +1 more source
Bayesian Self‐Optimization for Telescoped Continuous Flow Synthesis
Angewandte Chemie International Edition, Volume 62, Issue 3, January 16, 2023., 2023 An autonomous continuous flow platform for the rapid development of multistep synthetic pathways is reported. New multipoint sampling and Bayesian optimization techniques were combined, enabling simultaneous identification of optimum reaction conditions within a pharmaceutical process. The short optimization times achieved are promising for development
Adam D. Clayton +9 more
wiley +1 more source