Results 51 to 60 of about 102,586 (261)
Developing and Comparing Machine Learning Algorithms for Music Recommendation
JOIV: International Journal on Informatics VisualizationThe increasing prevalence of song skipping in music streaming applications negatively impacts user satisfaction and subscription retention. Dissatisfaction often arises when users encounter songs they actively dislike, highlighting a gap between user ...
Yoon-Teck Bau +2 more
doaj +1 more source
The R Journal, 2023 Gaussian mixture models (GMMs) are widely used for modelling stochastic problems. Indeed, a wide diversity of packages have been developed in R. However, no recent review describing the main features offered by these packages and comparing their performances has been performed.
Chassagnol, Bastien +7 more
openaire +2 more sources
Additive Gaussian Process Regression for Predictive Design of High‐Performance, Printable Silicones
Advanced Engineering Materials, EarlyView.A chemistry‐aware design framework for tuning printable polydimethylsiloxane (PDMS) for vat photopolymerization (VPP) is developed using additive Gaussian process (GP) modeling. Polymer network mechanics informs variable groupings, feasible formulation constraints, and interaction variables.
Roxana Carbonell +3 more
wiley +1 more source
Tangles were originally introduced as a concept to formalize regions of high connectivity in graphs. In recent years, they have also been discovered as a link between structural graph theory and data science: when interpreting similarity in data sets as connectivity between points, finding clusters in the data essentially amounts to finding tangles in ...
Eva Fluck +2 more
openaire +2 more sources
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Diffusion model conditioning on Gaussian mixture model and negative Gaussian mixture gradient
NeurocomputingDiffusion models (DMs) are a type of generative model that has a huge impact on image synthesis and beyond. They achieve state-of-the-art generation results in various generative tasks. A great diversity of conditioning inputs, such as text or bounding boxes, are accessible to control the generation.
Weiguo Lu +5 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Gaussian mixture model of heart rate variability. [PDF]
PLoS ONE, 2012 Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition.
Tommaso Costa +2 more
doaj +1 more source
On the Properties of Gaussian Copula Mixture Models
Advances in Artificial Intelligence and Machine Learning, 2023 11 pages paper for theoretical properties and new algorithms for ...
Ke Wan 0001, Alain L. Kornhauser
openaire +2 more sources
Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying
Advanced Engineering Materials, EarlyView.An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara +8 more
wiley +1 more source