Results 31 to 40 of about 2,902,077 (302)
Bottleneck Conditional Density Estimation
We introduce a new framework for training deep generative models for high-dimensional conditional density estimation. The Bottleneck Conditional Density Estimator (BCDE) is a variant of the conditional variational autoencoder (CVAE) that employs layer(s) of stochastic variables as the bottleneck between the input $x$ and target $y$, where both are high-
Rui Shu +2 more
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Nonparametric Estimation of the Density Function of the Distribution of the Noise in CHARN Models
This work is concerned with multivariate conditional heteroscedastic autoregressive nonlinear (CHARN) models with an unknown conditional mean function, conditional variance matrix function and density function of the distribution of noise.
Joseph Ngatchou-Wandji +3 more
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Interpolating Conditional Density Trees
Appears in Proceedings of the Eighteenth Conference on Uncertainty in Artificial Intelligence (UAI2002)
Scott Davies, Andrew W. Moore 0001
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Density Conditions For Triangles In Multipartite Graphs
We consider the problem of finding a large or dense triangle-free subgraph in a given graph $G$. In response to a question of P. Erd\H{o}s, we prove that, if the minimum degree of $G$ is at least $17|V(G)|/20 $, the largest triangle-free subgraphs are precisely the largest bipartite subgraphs in $G$. We investigate in particular the case where $G$ is a
J. Adrian Bondy +3 more
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Conditional Densities of Regular Languages
AbstractWe define a density of a given language S in a given language L as an asymptotic probability that a randomly and uniformly chosen word of length n from L belongs to S. There are languages for which densities do not exist. We show that a problem of checking whether one regular language has a density in another regular language is decidable.
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A probabilistic prediction of the next strong earthquake in the Acapulco-San Marcos segment, Mexico [PDF]
Conditional probabilities for recurrence times of large earthquakes are a reasonable and valid form for estimating the likelihood of future large earthquakes.
Sergio G. Ferráes
doaj
The main objective of this paper is to investigate the nonparametric estimation of the conditional density of a scalar response variable Y, given the explanatory variable X taking value in a Hilbert space when the sample of observations is considered as ...
Fatima Akkal, Nadia Kadiri, Abbes Rabhi
doaj
In the literature, we can find several blind adaptive deconvolution algorithms based on closed-form approximated expressions for the conditional expectation (the expectation of the source input given the equalized or deconvolutional output), involving ...
Monika Pinchas
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High-Resolution Crowd Density Maps Generation With Multi-Scale Fusion Conditional GAN
The major challenges for density maps estimation and accurate counting stem from the large-scale variations, serious occlusions, and perspective distortions.
Shaonian Huang +3 more
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Nonparametric estimation for a probability density function that describes multivariate data has typically been addressed by kernel density estimation (KDE).
Jenny Farmer +2 more
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