Results 131 to 140 of about 1,249,090 (302)
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Bayesian Analysis for Penalized Spline Regression Using WinBUGS [PDF]
Penalized splines can be viewed as BLUPs in a mixed model framework, which allows the use of mixed model software for smoothing. Thus, software originally developed for Bayesian analysis of mixed models can be used for penalized spline regression ...
Ciprian M. Crainiceanu +2 more
core +1 more source
Unveiling Localized Heat in Lithium‐Ion Cells for Intelligent Temperature Sensing
Advanced Energy and Sustainability Research, EarlyView.Heat generation, thermal responses, and intelligent management in batteries. Lithium‐ion batteries (LIBs) power electric vehicles, portable electronics, and grid‐scale storage, yet their safety, performance, and lifetime are constrained by thermal effects.
Yunke Wang +6 more
wiley +1 more source
MRBAYES: Bayesian inference of phylogenetic trees
Bioinform., 2001 J. Huelsenbeck, F. Ronquist
semanticscholar +1 more source
Agribusiness, EarlyView.ABSTRACT This study investigates the financial literacy (FL) of Swedish farmers, its linkages to farmer characteristics, management accounting practices and farm outcomes by surveying Swedish Farm Accountancy Data Network farmers. Using item response theory, we expand the existing FL measurement specifically to the farming context, assess measurement ...
Uliana Gottlieb, Helena Hansson
wiley +1 more source
Multivariate Student -t Regression Models: Pitfalls and Inference [PDF]
We consider likelihood-based inference from multivariate regression models with independent Student-t errors. Some very intruiging pitfalls of both Bayesian and classical methods on the basis of point observations are uncovered. Bayesian inference may be
Fernández, C., Steel, M.F.J.
core +1 more source
Agribusiness, EarlyView.ABSTRACT Vending is an important sector in the daily lives of many people, and coffee is the most frequently consumed product in the European market. Like many other sectors, vending is responding to the challenge of sustainable development by taking various actions, such as offering increasingly ecologically sound coffee while maintaining/improving ...
Alberto Bertossi +2 more
wiley +1 more source
MrBayes 3: Bayesian phylogenetic inference under mixed models
Bioinform., 2003 F. Ronquist, J. Huelsenbeck
semanticscholar +1 more source
Bayesian inference for bivariate ranks
, 2018 A recommender system based on ranks is proposed, where an expert's ranking of a set of objects and a user's ranking of a subset of those objects are combined to make a prediction of the user's ranking of all objects.
Guillotte, Simon +2 more
core
Agribusiness, EarlyView.ABSTRACT The US hemp market is a new and nascent industry that has been devoid of research for about half a century. This study examined the effects of exogenous shock on price at each phase of the value chain—Farm (hemp biomass), and its impact on prices at other phases of the value chain—Intermediary Processor (crude cannabidiol hemp) and Final ...
Solomon Odiase +2 more
wiley +1 more source