Results 31 to 40 of about 523,565 (314)
Predicting Facial Biotypes Using Continuous Bayesian Network Classifiers
Complexity, 2018 Bayesian networks are useful machine learning techniques that are able to combine quantitative modeling, through probability theory, with qualitative modeling, through graph theory for visualization.
Gonzalo A. Ruz, Pamela Araya-Díaz
doaj +1 more source
Bayesian Policy Gradients via Alpha Divergence Dropout Inference
, 2011 Policy gradient methods have had great success in solving continuous control tasks, yet the stochastic nature of such problems makes deterministic value estimation difficult.
Henderson, Peter +3 more
core +3 more sources
Opinion Dynamics with Bayesian Learning
Complexity, 2020 Bayesian learning is a rational and effective strategy in the opinion dynamic process. In this paper, we theoretically prove that individual Bayesian learning can realize asymptotic learning and we test it by simulations on the Zachary network.
Aili Fang +3 more
doaj +1 more source
Network Plasticity as Bayesian Inference
, 2015 General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing.
Habenschuss, Stefan +3 more
core +3 more sources
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
doaj +1 more source
Addressing Economic Insecurities Can Improve Patient‐Reported Outcomes in Lupus
Arthritis Care &Research, Accepted Article.Background Economic insecurities, such as food, housing, transportation, and financial challenges, are modifiable risk factors and influence patient‐reported outcomes (PROs) in systemic lupus erythematosus (SLE). We examined: 1) associations between economic insecurities and PROs; 2) the impact of screening and addressing economic insecurities during ...
Jay Patel +8 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
openaire +2 more sources
High Healthcare Utilization Preceding Diagnosis with Juvenile Idiopathic Arthritis
Arthritis Care &Research, Accepted Article.Objective Though early diagnosis improves long‐term outcomes, Juvenile Idiopathic Arthritis (JIA) patients often experience prolonged, circuitous paths to diagnosis. To inform diagnostic improvement, we sought to characterize healthcare utilization in the year preceding diagnosis.
Anna Costello +5 more
wiley +1 more source
Cutset Sampling for Bayesian Networks
, 2011 The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network structure-exploiting application of the Rao-Blackwellisation principle to ...
Bidyuk, B., Dechter, R.
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Advanced Functional Materials, EarlyView.This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak +14 more
wiley +1 more source