Nov 20, 2023 · Based on this, we introduce a Gaussian mixture model (GMM) with multiple reference points and derive the maximum likelihood estimator.
This includes intrinsic models on the manifold of symmetric positive definite (SPD) matrices such as the Riemannian Gaussian distribution, but also conventional.
We introduce a Gaussian mixture model (GMM) with multiple reference points and derive the maximum likelihood estimator.
Gaussian mixture models (GMM) are widely used for image segmentation. The bigger the number in the mixture, the higher will be the data likelihood.
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Vorba et al. [2014] used a 2D Gaussian mixture to model incident radiance distribution; however, since the domain of a 2D Gaussian is the entire 2D plane, when ...
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Apr 25, 2024 · A Gaussian mixture model with multiple tangent planes. EUSIPCO 2023 ... Yannick Berthoumieu: Deep Ensemble Learning Model Based on Covariance ...
A Gaussian mixture model is a soft clustering technique used in unsupervised learning to determine the probability that a given data point belongs to a cluster.
These results clearly show the advantage of using multiple tangent planes to better approximate manifold distributions. ... Fisher distributions (vMF), a single ...
These results clearly show the advantage of using multiple tangent planes to better approximate manifold distributions. ... Fisher distributions (vMF), a single ...
Jun 20, 2022 · Consider, for example, a gaussian model is regular but a mixture model thereof is not identifiable. An exponential family with non-minimal ...