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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
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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
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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
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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
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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
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Medical Image Registration Algorithm Based on Bounded Generalized Gaussian Mixture Model [PDF]
Frontiers in Neuroscience, 2022 In this paper, a method for medical image registration based on the bounded generalized Gaussian mixture model is proposed. The bounded generalized Gaussian mixture model is used to approach the joint intensity of source medical images. The mixture model
Jingkun Wang +6 more
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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
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. [PDF]
PLoS ONEIn the field of robotic arm trajectory imitation learning, Gaussian Mixture Models are widely used for their ability to capture the characteristics of complex trajectories. However, one major challenge in utilizing these models lies in the initialization
Jingnan Yan +4 more
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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
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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
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