Crowdsourcing aggregation with deep Bayesian learning
Sign Up to like & getrecommendations! Published in 2021 at "Science China Information Sciences"
DOI: 10.1007/s11432-020-3118-7
Abstract: In this study, we consider a crowdsourcing classification problem in which labeling information from crowds is aggregated to infer latent true labels. We propose a fully Bayesian deep generative crowdsourcing model (BayesDGC), which combines the… read more here.
Keywords: deep bayesian; crowdsourcing aggregation; latent true; bayesian learning ... See more keywords
Sparse Bayesian learning approach for baseline correction
Sign Up to like & getrecommendations! Published in 2020 at "Chemometrics and Intelligent Laboratory Systems"
DOI: 10.1016/j.chemolab.2020.104088
Abstract: Abstract Spectral techniques in analytical chemistry are often affected by baselines in practical implementation. Without baseline correction, the accuracy of the qualitative/quantitative analytical results may degrade substantially. Sparse representation has been applied to baseline correction… read more here.
Keywords: baseline correction; correction; sparse bayesian; performance ... See more keywords
An efficient and robust adaptive sampling method for polynomial chaos expansion in sparse Bayesian learning framework
Sign Up to like & getrecommendations! Published in 2019 at "Computer Methods in Applied Mechanics and Engineering"
DOI: 10.1016/j.cma.2019.04.046
Abstract: Abstract Sparse polynomial chaos expansion has been widely used to tackle problems of function approximation in the field of uncertain quantification. The accuracy of PCE depends on how to construct the experimental design. Therefore, adaptive… read more here.
Keywords: chaos expansion; polynomial chaos; sparse bayesian; adaptive sampling ... See more keywords
A non-negative Bayesian learning method for impact force reconstruction
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Sound and Vibration"
DOI: 10.1016/j.jsv.2019.06.013
Abstract: Abstract Detecting and identifying impact events, which may cause severe damages, is important in assessment of the integrity of many engineering structures. This paper presents a new approach for reconstructing the impact forces applied on… read more here.
Keywords: impact force; impact; non negative; force reconstruction ... See more keywords
Sparse Bayesian learning for structural damage identification
Sign Up to like & getrecommendations! Published in 2020 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2020.106689
Abstract: Abstract Identification of structural parameters can be cast as the process of solving an inverse problem, in which regularization may be required when the problem is ill-posed. Bayesian inference provides a probabilistic interpretation of the… read more here.
Keywords: structural damage; damage identification; sparse bayesian; identification ... See more keywords
Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks
Sign Up to like & getrecommendations! Published in 2020 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.0c00416
Abstract: This work considers strategies to develop accurate and reliable graph neural networks (GNNs) for molecular property predictions. Prediction performance of GNNs is highly sensitive to the change in various parameters due to the inherent challenges… read more here.
Keywords: neural networks; study; graph neural; supervised learning ... See more keywords
Bayesian Learning of Adatom Interactions from Atomically Resolved Imaging Data.
Sign Up to like & getrecommendations! Published in 2021 at "ACS nano"
DOI: 10.1021/acsnano.0c10851
Abstract: Atomic structures and adatom geometries of surfaces encode information about the thermodynamics and kinetics of the processes that lead to their formation, and which can be captured by a generative physical model. Here we develop… read more here.
Keywords: resolved imaging; interactions atomically; adatom interactions; atomically resolved ... See more keywords
Sparse Bayesian learning for spinning antenna DOA super-resolution
Sign Up to like & getrecommendations! Published in 2018 at "Electronics Letters"
DOI: 10.1049/el.2017.4010
Abstract: The spinning, wide bandwidth antenna remains the most cost-effective technique for finding the direction of arrival of emitters’ signals. The beam is broadest at the low edge of the monitored band, resulting in poor angular… read more here.
Keywords: resolution; spinning antenna; super resolution; sparse bayesian ... See more keywords
Melodic patterns and tonal cadences: Bayesian learning of cadential categories from contrapuntal information
Sign Up to like & getrecommendations! Published in 2019 at "Journal of New Music Research"
DOI: 10.1080/09298215.2019.1607396
Abstract: ABSTRACT Recent work has shown that authentic and half cadences can be identified via harmonic features in both supervised and unsupervised settings, suggesting that humans may use such cues in perceiving and learning cadences. The… read more here.
Keywords: learning cadential; patterns tonal; tonal cadences; cadences bayesian ... See more keywords
Trust your gut: using physiological states as a source of information is almost as effective as optimal Bayesian learning
Sign Up to like & getrecommendations! Published in 2018 at "Proceedings of the Royal Society B: Biological Sciences"
DOI: 10.1098/rspb.2017.2411
Abstract: Approaches to understanding adaptive behaviour often assume that animals have perfect information about environmental conditions or are capable of sophisticated learning. If such learning abilities are costly, however, natural selection will favour simpler mechanisms for… read more here.
Keywords: information; environmental conditions; source information; states source ... See more keywords
Lattice protein design using Bayesian learning
Sign Up to like & getrecommendations! Published in 2021 at "Physical review. E"
DOI: 10.1103/physreve.104.014404
Abstract: Protein design is the inverse approach of the three-dimensional (3D) structure prediction for elucidating the relationship between the 3D structures and amino acid sequences. In general, the computation of the protein design involves a double… read more here.
Keywords: protein design; lattice; amino acid; design ... See more keywords