Results 51 to 60 of about 182,801 (272)
Biclustering microarray data by Gibbs sampling [PDF]
Bioinformatics, 2003 Abstract Motivation: Gibbs sampling has become a method of choice for the discovery of noisy patterns, known as motifs, in DNA and protein sequences. Because handling noise in microarray data presents similar challenges, we have adapted this strategy to the biclustering of discretized microarray data.
Qizheng, Sheng +2 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.A carbon‐free, as‐sintered MgO–steel cermet anode, fabricated via cold isostatic pressing using MgO–C refractory recyclate, was evaluated under laboratory‐scale K‐cryolite electrolysis at 800°C. Operation at this reduced temperature, combined with the electrolyte's limited electrical conductivity, led to an increase in cell voltage.
Farhan Hossain +7 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.This paper presents a novel approach to reducing oxide layers on metal powders using low‐temperature hydrogen dielectric barrier discharge plasmas at atmospheric pressure. Unlike conventional hydrogen‐plasma reductions, the powders do not contact the plasma directly.
Shukang Zhang +3 more
wiley +1 more source
Learnable Markov Chain Monte Carlo Sampling Methods for Lattice Gaussian Distribution
IEEE Access, 2019 As a key ingredient of machine learning and artificial intelligence, the sampling algorithms with respect to lattice Gaussian distribution has emerged as an important problem in coding and decoding of wireless communications.
Zheng Wang, Shanxiang Lyu, Ling Liu
doaj +1 more source
The Gibbs Sampler with Particle Efficient Importance Sampling for State-Space Models
, 2018 We consider Particle Gibbs (PG) as a tool for Bayesian analysis of non-linear non-Gaussian state-space models. PG is a Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the Gibbs ...
Grothe, Oliver +2 more
core +1 more source
Advanced Engineering Materials, EarlyView.This study investigates how tramp elements from increased scrap usage influence phase transformations in low‐alloyed steel. Combining dilatometry and microscopy reveal that tramp elements delay transformations, reduce critical cooling rates and increase hardenability.
Lukas Hatzenbichler +5 more
wiley +1 more source
Genetics Selection Evolution, 2007 Simulated data were used to investigate the influence of the choice of priors on estimation of genetic parameters in multivariate threshold models using Gibbs sampling.
Hoeschele Ina +2 more
doaj +1 more source
Performance of the No-U-Turn sampler in multi-trait variance component estimation using genomic data
Genetics Selection Evolution, 2022 Background Multi-trait genetic parameter estimation is an important topic for target traits with few records and with a low heritability and when the genetic correlation between target and secondary traits is strong.
Motohide Nishio, Aisaku Arakawa
doaj +1 more source
Astronomy & Astrophysics, 2023 We present a Gibbs sampling solution to the mapmaking problem for cosmic microwave background (CMB) measurements that builds on existing destriping methodology. Gibbs sampling breaks the computationally heavy destriping problem into two separate steps: noise filtering and map binning.
E. Keihänen +41 more
openaire +6 more sources
Incorporating Discriminator in Sentence Generation: a Gibbs Sampling Method
, 2018 Generating plausible and fluent sentence with desired properties has long been a challenge. Most of the recent works use recurrent neural networks (RNNs) and their variants to predict following words given previous sequence and target label.
Huang, Xuanjing +3 more
core +1 more source