Results 41 to 50 of about 844,595 (275)
In this paper we introduce deep Gaussian process (GP) models. Deep GPs are a deep belief network based on Gaussian process mappings. The data is modeled as the output of a multivariate GP.
Damianou, Andreas C., Lawrence, Neil D.
core
Palm distributions for log Gaussian Cox processes [PDF]
This paper establishes a remarkable result regarding Palmdistributions for a log Gaussian Cox process: the reduced Palmdistribution for a log Gaussian Cox process is itself a log Gaussian Coxprocess which only differs from the original log Gaussian Cox ...
Coeurjolly, Jean-François +2 more
core +4 more sources
Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
WLAN monopole antenna design by Siamese convolutional neural network and KNN exploiting Gaussian process [PDF]
In the process of antenna design, surrogate models can generally be used, but modeling requires a large number of samples. Although full wave electromagnetic simulation software can handle this task, obtaining a large number of samples is time-consuming,
Tian Yubo, Meng Fei
doaj +1 more source
On the Construction of Some Fractional Stochastic Gompertz Models
The aim of this paper is the construction of stochastic versions for some fractional Gompertz curves. To do this, we first study a class of linear fractional-integral stochastic equations, proving existence and uniqueness of a Gaussian solution.
Giacomo Ascione, Enrica Pirozzi
doaj +1 more source
Induction of diabetes in three different mouse strains uniformly resulted in an increase in TNAP activity and a reduction in pyrophosphate (PPi) in the circulation. Inhibition of TNAP restored plasma PPi. Diabetes‐induced calcification in the media layer of the aorta was detected only in the Abcc6−/− strain, which is predisposed to ectopic ...
Krisztina Fülöp +13 more
wiley +1 more source
In this paper, we propose a novel approach to undertake the colorimetric camera characterization procedure based on a Gaussian process (GP). GPs are powerful and flexible nonparametric models for multivariate nonlinear functions. To validate the GP model,
Adolfo Molada-Tebar +3 more
doaj +1 more source
Student-t Processes as Alternatives to Gaussian Processes [PDF]
We investigate the Student-t process as an alternative to the Gaussian process as a nonparametric prior over functions. We derive closed form expressions for the marginal likelihood and predictive distribution of a Student-t process, by integrating away ...
Ghahramani, Zoubin +2 more
core +1 more source
Strong Approximation of Empirical Copula Processes by Gaussian Processes
We provide the strong approximation of empirical copula processes by a Gaussian process. In addition we establish a strong approximation of the smoothed empirical copula processes and a law of iterated ...
Adler R. J. +21 more
core +1 more source
Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source

