Results 1 to 10 of about 471,639 (138)

Sparse bayesian learning for genomic selection in yeast [PDF]

open access: yesFrontiers in Bioinformatics, 2022
Genomic selection, which predicts phenotypes such as yield and drought resistance in crops from high-density markers positioned throughout the genome of the varieties, is moving towards machine learning techniques to make predictions on complex traits ...
Maryam Ayat, Mike Domaratzki
doaj   +2 more sources

A hybrid algorithm for Bayesian network structure learning with application to multi-label learning [PDF]

open access: yesExpert Systems With Applications, 2014
We present a novel hybrid algorithm for Bayesian network structure learning, called H2PC. It first reconstructs the skeleton of a Bayesian network and then performs a Bayesian-scoring greedy hill-climbing search to orient the edges.
Maxime Gasse   +2 more
exaly   +7 more sources

Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings. [PDF]

open access: yesPLoS Computational Biology, 2011
Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free) reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty.
Elise Payzan-LeNestour, Peter Bossaerts
doaj   +8 more sources

Bayesian Uncertainty Quantification for Channelized Reservoirs via Reduced Dimensional Parameterization

open access: yesMathematics, 2021
In this article, we study uncertainty quantification for flows in heterogeneous porous media. We use a Bayesian approach where the solution to the inverse problem is given by the posterior distribution of the permeability field given the flow and ...
Anirban Mondal, Jia Wei
doaj   +1 more source

The Aggregate Impact of Consumer Reviews on Market Outcome in Differentiated Products Market

open access: yesAsia Marketing Journal, 2021
The Aggregate Impact of Consumer Reviews on Market Outcome in Differentiated Products Market Jun B. Kim, Seoul National University, Republic of KoreaFollow Abstract We investigate the aggregate impact of consumer reviews on market outcome in a ...
Jun B. Kim
doaj   +1 more source

Bayesian localization for autonomous vehicle using sensor fusion and traffic signs [PDF]

open access: yesКомпьютерные исследования и моделирование, 2018
The localization of a vehicle is an important task in the field of intelligent transportation systems. It is well known that sensor fusion helps to create more robust and accurate systems for autonomous vehicles. Standard approaches, like extended Kalman
Sergey I. Verentsov   +5 more
doaj   +1 more source

AVA: A Financial Service Chatbot Based on Deep Bidirectional Transformers

open access: yesFrontiers in Applied Mathematics and Statistics, 2021
We develop a chatbot using deep bidirectional transformer (BERT) models to handle client questions in financial investment customer service. The bot can recognize 381 intents, decides when to say I don’t know, and escalate escalation/uncertain questions ...
Shi Yu, Yuxin Chen, Hussain Zaidi
doaj   +1 more source

Prediction for Manufacturing Factors in a Steel Plate Rolling Smart Factory Using Data Clustering-Based Machine Learning

open access: yesIEEE Access, 2020
A Steel Plate Rolling Mill (SPM) is a milling machine that uses rollers to press hot slab inputs to produce ferrous or non-ferrous metal plates. To produce high-quality steel plates, it is important to precisely detect and sense values of manufacturing ...
Cheol Young Park   +3 more
doaj   +1 more source

Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity [PDF]

open access: yesOpen Biology, 2014
One goal of cell biology is to understand how cells adopt different shapes in response to varying environmental and cellular conditions. Achieving a comprehensive understanding of the relationship between cell shape and environment requires a systems ...
Heba Sailem   +3 more
doaj   +1 more source

On Sequential Bayesian Inference for Continual Learning

open access: yesEntropy, 2023
Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks.
Samuel Kessler   +4 more
doaj   +1 more source

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