Results 1 to 10 of about 901,615 (325)
Classifying Exoplanets with a Gaussian Mixture Model [PDF]
The Open Journal of Astrophysics, 2018 Recently, Odrzywolek and Rafelski 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 ...
Soham Kulkarni, Shantanu Desai
doaj +5 more sources
Deep Gaussian Mixture Models [PDF]
Statistics and Computing, 2017 Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, Deep Gaussian Mixture Models are introduced and discussed.
McLachlan, Geoffrey J., Viroli, Cinzia
core +6 more sources
Model Selection for Gaussian Mixture Models [PDF]
Statistica Sinica, 2013 This paper is concerned with an important issue in finite mixture modelling, the selection of the number of mixing components. We propose a new penalized likelihood method for model selection of finite multivariate Gaussian mixture models.
Huang, Tao, Peng, Heng, Zhang, Kun
core +4 more sources
A Fast Incremental Gaussian Mixture Model. [PDF]
PLoS ONE, 2015 This work builds upon previous efforts in online incremental learning, namely the Incremental Gaussian Mixture Network (IGMN). The IGMN is capable of learning from data streams in a single-pass by improving its model after analyzing each data point and ...
Rafael Coimbra Pinto +1 more
doaj +5 more sources
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 +6 more sources
IMAGE SEGMENTATION USING GAUSSIAN MIXTURE MODEL
International Journal of Industrial Engineering and Production Research, 2008 Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we have learned Gaussian mixture model to the pixels of an image. The parameters of the
Rahman Farnoosh, Behnam Zarpak
doaj +3 more sources
Intrinsically Interpretable Gaussian Mixture Model
Information, 2023 Understanding the reasoning behind a predictive model’s decision is an important and longstanding problem driven by ethical and legal considerations.
Nourah Alangari +3 more
doaj +1 more source
Gaussian Mixture Model for Marine Reverberations
Applied Sciences, 2023 Ocean reverberations, a significant interference source in active sonar, arise as a response generated by random scattering at the receiving end, a consequence of randomly distributed clutter or irregular interfaces. Statistical analysis of reverberation
Tongjing Sun +4 more
doaj +1 more source
Quantum-like Gaussian mixture model [PDF]
Soft Computing, 2021 Abstract A new concept of a quantum-like mixture model is introduced. It describes the mixture distribution with the assumption that a point is generated by each Gaussian at the same time. The decision boundary of a quantum-like mixture Gaussian corresponds as well to the separation of probabilities for the switching Kalman filter. The quantum-
openaire +2 more sources
Entropy-Based Anomaly Detection for Gaussian Mixture Modeling
Algorithms, 2023 Gaussian mixture modeling is a generative probabilistic model that assumes that the observed data are generated from a mixture of multiple Gaussian distributions. This mixture model provides a flexible approach to model complex distributions that may not
Luca Scrucca
doaj +1 more source