Results 61 to 70 of about 298,891 (271)

Nonmonotonic Generalization Bias of Gaussian Mixture Models [PDF]

Neural Computation, 2000
Theories of learning and generalization hold that the generalization bias, defined as the difference between the training error and the generalization error, increases on average with the number of adaptive parameters. This article, however, shows that this general tendency is violated for a gaussian mixture model. For temperatures just below the first
Akaho, S., Kappen, H.J.
openaire   +4 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, Martha Leach, Hongtao Song, Carolyn Seepersad   +3 more
wiley   +1 more source

Classifying Exoplanets with Gaussian Mixture Model [PDF]

The Open Journal of Astrophysics, 2018
Recently, Odrzywolek and Rafelski (arXiv:1612.03556) have found three distinct categories of exoplanets, when they are classified based on density. We first carry out a similar classification of exoplanets according to their density using the Gaussian Mixture Model, followed by information theoretic criterion (AIC and BIC) to determine the optimum ...
Soham Kulkarni, Shantanu Desai
openaire   +4 more sources

Effect of Laser Deoxidation on Adhesive‐Bonded Aluminum in an Oxygen‐Free Atmosphere

Advanced Engineering Materials, EarlyView.
This study investigates laser ablation of aluminum under oxygen‐free conditions. The goal is to produce oxide‐free substrates that enable improved adhesive bonding with epoxy. Optimized laser parameters (90% overlap, 300 µJ) combined with oxide‐free substrates result in the highest tensile strength of the adhesive bond.
Sandra Gerland, Finn‐Lennard Janthur, Sarah Seffer, Jörg Hermsdorf, Ludger Overmeyer, Annika Raatz   +5 more
wiley   +1 more source

Application of the Gaussian Mixture Model to Classify Stages of Electrical Tree Growth in Epoxy Resin

Sensors, 2021
In high-voltage (HV) insulation, electrical trees are an important degradation phenomenon strongly linked to partial discharge (PD) activity. Their initiation and development have attracted the attention of the research community and better understanding
Abdullahi Abubakar Mas’ud, Arunachalam Sundaram, Jorge Alfredo Ardila-Rey, Roger Schurch, Firdaus Muhammad-Sukki, Nurul Aini Bani   +5 more
doaj   +1 more source

Gaussian mixture 3D morphable face model

Pattern Recognition, 2018
A Gaussian Mixture 3DMM (GM-3DMM) which models the global population as a mixture of Gaussian subpopulations.A ESO-based model selection strategy for GM-3DMM fitting.A GM-3DMM-based face recognition framework by fusing multiple experts, which has achieved state-of-the-art result on the Multi-PIE face dataset.A new 3D face dataset, SURREY-JNU ...
Koppen, Paul, Feng, Zhenhua, Kittler, Josef, Awais, Muhammad, Christmas, William, Wu, Xiao-Jun, Yin, He-Feng   +6 more
openaire   +3 more sources

Al–Cu Composite Casting of Laser‐Deoxidized Copper: Bonding, Interfacial Chemistry, and Thermal Conductivity

Advanced Engineering Materials, EarlyView.
This study investigates laser‐based oxide removal of Cu inserts in oxygen‐free conditions and examines long‐term oxidation kinetics and surface chemistry under different atmospheres via X‐ray photoelectron spectroscopy. Al–Cu compound casting with differently oxidized surfaces is performed, and intermetallic phase formation, morphology, and thermal ...
Timon Steinhoff, Finn‐Lennard Janthur, Sascha Zimmermann, Sarah Seffer, Jörg Hermsdorf, René Gustus, Ludger Overmeyer, Wolfgang Maus‐Friedrichs, Hans Jürgen Maier, Christian Klose   +9 more
wiley   +1 more source

Bayesian inference of Gaussian mixture models with noninformative priors [PDF]

, 2014
This paper deals with Bayesian inference of a mixture of Gaussian distributions. A novel formulation of the mixture model is introduced, which includes the prior constraint that each Gaussian component is always assigned a minimal number of data points ...
Stoneking, Colin J.
core  

Investigation of Oxygen‐Free Wetting Behavior of Aluminum on Copper via Molecular Dynamics Simulations and Experiments

Advanced Engineering Materials, EarlyView.
The wettability of aluminum droplets (Al) on different copper substrates (Cu), where liquid Al spreads on solid Cu surfaces to form a liquid–solid interface, is studied numerically and experimentally. The experimental and numerical results show good agreement in the fast‐spreading regime.
Shan Lyu, Timon Steinhoff, Finn‐Lennard Janthur, Sarah Seffer, Jörg Hermsdorf, Christian Klose, Ludger Overmeyer, Hans‐Jürgen Maier, Nina Merkert   +8 more
wiley   +1 more source

Evaluation of Value-at-Risk (VaR) using the Gaussian Mixture Models

Research in Statistics
The normality of the distribution of stock returns is one of the basic assumptions in financial mathematics. Empirical studies, however, undermine the validity of this assumption.
Indrė Morkūnaitė, Dmitrij Celov, Remigijus Leipus   +2 more
doaj   +1 more source