Optimal Transport for Gaussian Mixture Models
نویسندگان
چکیده
منابع مشابه
Optimal transport for Gaussian mixture models
We present an optimal mass transport framework on the space of Gaussian mixture models, which are widely used in statistical inference. Our method leads to a natural way to compare, interpolate and average Gaussian mixture models. Basically, we study such models on a certain submanifold of probability densities with certain structure. Different aspects of this framework are discussed and severa...
متن کاملOptimal Transport Mixing of Gaussian Texture Models
This paper tackles the problem of mixing color texture models learned from an input dataset. We focus on stationary Gaussian texture models, also known as spot noises. We derive the barycenter and geodesic path between models according to optimal transport. This allows the user to navigate inside the set of texture models, and perform texture synthesis from the obtained interpolated models. Num...
متن کاملBayesian Growing and Pruning Strategies for Map-optimal Estimation of Gaussian Mixture Models Bayesian Growing and Pruning Strategies for Map-optimal Estimation of Gaussian Mixture Models
Real-time learning requires on-line complexity estimation. Expectation-maximisation (EM) and sampling techniques are presented that enable simultaneous estimation of the complexity and continuous parameters of Gaussian mixture models (GMMs) which can be used for density estimation, classiication and feature extraction. The solution is a maximum a posteriori probability (MAP) estimator that is c...
متن کاملFuzzy Gaussian Mixture Models
In this paper, in order to improve both the performance and the efficiency of the conventional Gaussian Mixture Models (GMMs), generalized GMMs are firstly introduced by integrating the conventional GMMs and the active curve axis GMMs for fitting non-linear datasets, and then two types of Fuzzy Gaussian Mixture Models (FGMMs) with a faster convergence process are proposed based on the generaliz...
متن کاملParsimonious Gaussian mixture models
Parsimonious Gaussian mixture models are developed using a latent Gaussian model which is closely related to the factor analysis model. These models provide a unified modeling framework which includes the mixtures of probabilistic principal component analyzers and mixtures of factor of analyzers models as special cases. In particular, a class of eight parsimonious Gaussian mixture models which ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2018.2889838