Results 31 to 40 of about 4,333,581 (301)
Asymptotic Convergence of Soft-Constrained Neural Networks for Density Estimation
Mathematics, 2020 A soft-constrained neural network for density estimation (SC-NN-4pdf) has recently been introduced to tackle the issues arising from the application of neural networks to density estimation problems (in particular, the satisfaction of the second ...
Edmondo Trentin
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Remote Sensing, 2020 We investigated nearest-neighbor density-based clustering for hyperspectral image analysis. Four existing techniques were considered that rely on a K-nearest neighbor (KNN) graph to estimate local density and to propagate labels through algorithm ...
Claude Cariou +2 more
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Multiscale Feature Adaptive Integration for Crowd Counting in Highly Congested Scenes
IEEE Access, 2022 Due to extreme scale variations in highly congested scenes, the accuracy of CNN-based crowd counting approaches still has considerable room for further improvements.
Hui Gao +4 more
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Default priors for density estimation with mixture models [PDF]
, 2010 The infinite mixture of normals model has become a popular method for density estimation problems. This paper proposes an alternative hierarchical model that leads to hyperparameters that can be interpreted as the location, scale and smoothness of the ...
Griffin, Jim E.
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The Estimation of Conditional Densities [PDF]
, 2000 We discuss a number of issues in the smoothed nonparametric estimation of kernel conditional probability density functions for stationary processes. The kernel conditional density estimate is a ratio of joint and marginal density estimates. We point out the different implications of leading choices of bandwidths in numerator and denominator for the ...
Xiaohong Chen +2 more
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Multiwavelet density estimation [PDF]
Applied Mathematics and Computation, 2013 Preprint
Florida Institute of Technology, Department of Physics and Space Sciences West University Blvd., Melbourne, FL 32901, USA ( host institution ) +2 more
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Density estimation trees [PDF]
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining, 2011 In this paper we develop density estimation trees (DETs), the natural analog of classification trees and regression trees, for the task of density estimation. We consider the estimation of a joint probability density function of a d-dimensional random vector X and define a piecewise constant estimator structured as a decision tree.
Parikshit Ram, Alexander G. Gray
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Featurized Density Ratio Estimation
CoRR, 2021 First two authors contributed ...
Kristy Choi +2 more
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Conditional density estimation with class probability estimators [PDF]
, 2009 Many regression schemes deliver a point estimate only, but often it is useful or even essential to quantify the uncertainty inherent in a prediction. If a conditional density estimate is available, then prediction intervals can be derived from it.
Remco R. Bouckaert +3 more
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Density estimates for Canada lynx vary among estimation methods
Ecosphere, 2021 Unbiased population density estimates are critical for ecological research and wildlife management but are often difficult to obtain. Researchers use a variety of sampling and statistical methods to generate estimates of density, but few studies have ...
D. DoranâMyers +8 more
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