Results 51 to 60 of about 471,788 (278)
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
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models
, 2015 Learning in deep models using Bayesian methods has generated significant attention recently. This is largely because of the feasibility of modern Bayesian methods to yield scalable learning and inference, while maintaining a measure of uncertainty in the
Carin, Lawrence +3 more
core +1 more source
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
Open Mathematics, 2018 The problem of structures learning in Bayesian networks is to discover a directed acyclic graph that in some sense is the best representation of the given database. Score-based learning algorithm is one of the important structure learning methods used to
Wang Jingyun, Liu Sanyang
doaj +1 more source
Bayesian Learning of Graph Substructures
Bayesian Analysis, 2023 41 pages, 8 ...
Boom, Willem van den +2 more
openaire +4 more sources
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Psychological evidence suggests that people’s learning behavior is often prone to a “myside bias”or “irrational belief persistence”in contrast to learning behavior exclusively based on objective data.
Ludwig, Alexander, Zimper, Alexander
core +3 more sources
Clinical, histological, and serological predictors of renal function loss in lupus nephritis.
Arthritis Care &Research, Accepted Article.Objective Kidney survival is the ultimate goal in lupus nephritis (LN) management, but long‐term predictors remain inadequately studied, requiring long‐term follow‐up. This study aimed to identify baseline and early longitudinal predictors of kidney survival in the Accelerating Medicines Partnership LN longitudinal cohort.
Shangzhu Zhang +21 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Non-Bayesian Social Learning With Imperfect Private Signal Structure
IEEE Access, 2019 As one of the classic models that describe the belief dynamics over social networks, a non-Bayesian social learning model assumes that members in the network possess accurate signal knowledge through the process of Bayesian inference.
Sannyuya Liu +3 more
doaj +1 more source