Results 41 to 50 of about 866,116 (323)

Deep Gaussian Processes [PDF]

, 2013
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  

A methionine‐lined active site governs carbocation stabilization and product specificity in a bacterial terpene synthase

FEBS Letters, EarlyView.
This study reveals a unique active site enriched in methionine residues and demonstrates that these residues play a critical role by stabilizing carbocation intermediates through novel sulfur–cation interactions. Structure‐guided mutagenesis further revealed variants with significantly altered product profiles, enhancing pseudopterosin formation. These
Marion Ringel, Carl P. O. Helmer, Shani Zev, Ronja Driller, Emily Buhr, Markus Reinbold, Renana Schwartz, Gabriel Foley, Mikael Boden, Daniel Garbe, Gerhard Schenk, Dan Thomas Major, Bernhard Loll, Thomas Brück   +13 more
wiley   +1 more source

WLAN monopole antenna design by Siamese convolutional neural network and KNN exploiting Gaussian process [PDF]

MATEC Web of Conferences
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

Mathematics, 2020
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

In vitro models of cancer‐associated fibroblast heterogeneity uncover subtype‐specific effects of CRISPR perturbations

Molecular Oncology, EarlyView.
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, Shamsudheen Karuthedath Vellarikkal, Lixia Li, Hong Sun, Khoa Nguyen, Amber Montano, Suchitra Natarajan, Federica Piccioni, Alex Michael Tamburino, Xin Yu, Aleksandra Katarzyna Olow   +10 more
wiley   +1 more source

A Gaussian Process Model for Color Camera Characterization: Assessment in Outdoor Levantine Rock Art Scenes

Sensors, 2019
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, Gabriel Riutort-Mayol, Ángel Marqués-Mateu, José Luis Lerma   +3 more
doaj   +1 more source

Strong Approximation of Empirical Copula Processes by Gaussian Processes

, 2011
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., Bouzebda S., Chung K.-L., Csörgő M., Csörgő M., Cui S., DasGupta A., Deheuvels P., Deheuvels P., Deheuvels P., Fermanian J.-D., Joe H., McNeil A. J., Moore D. S., Nelsen R. B., Piterbarg V. I., Salim Bouzebda, Shorack G. R., Sklar A., Sklar A., Tarek Zari, Tsukahara H.   +21 more
core   +1 more source

Polarization‐resolved femtosecond Vis/IR spectroscopy tailored for resolving weak signals in biological samples using minimal sample volume

FEBS Open Bio, EarlyView.
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

Distributed Gaussian Processes With Uncertain Inputs

IEEE Access
Gaussian Process regression is a powerful non-parametric approach that facilitates probabilistic uncertainty quantification in machine learning. Distributed Gaussian Process (DGP) methods offer scalable solutions by dividing data among multiple GP models
Peter L. Green
doaj   +1 more source

A comparison of geometric- and regression-based mobile gaze-tracking

Frontiers in Human Neuroscience, 2014
Video-based gaze-tracking systems are typically restricted in terms of their effective tracking space. This constraint limits the use of eyetrackers in studying mobile human behavior.
Björn eBrowatzki, Heinrich H. Bülthoff, Heinrich H. Bülthoff, Lewis L. Chuang   +3 more
doaj   +1 more source