Results 31 to 40 of about 12,640,042 (291)

Estimating Road Segments Using Kernelized Averaging of GPS Trajectories

Applied Sciences, 2019
A method called iTEKA, which stands for iterative time elastic kernel averaging, was successfully used for averaging time series. In this paper, we adapt it to GPS trajectories. The key contribution is a denoising procedure that includes an over-sampling
Pierre-François Marteau
doaj   +1 more source

Bayesian Kernel Methods

, 2003
Bayesian methods allow for a simple and intuitive representation of the function spaces used by kernel methods. This chapter describes the basic principles of Gaussian Processes, their implementation and their connection to other kernel-based Bayesian estimation methods, such as the Relevance Vector Machine.
Alexander J. Smola, Bernhard Schölkopf
openaire   +3 more sources

Rate-Distortion Bounds for Kernel-Based Distortion Measures

Entropy, 2017
Kernel methods have been used for turning linear learning algorithms into nonlinear ones. These nonlinear algorithms measure distances between data points by the distance in the kernel-induced feature space.
Kazuho Watanabe
doaj   +1 more source

COMPARATION ON SEVERAL SMOOTHING METHODS IN NONPARAMETRIC REGRESSION [PDF]

, 2011
There are three nonparametric regression methods covered in this section. These are Moving Average Filtering-Based Smoothing, Local Regression Smoothing, and Kernel Smoothing Methods.
Isnanto, R.Rizal, Rizal Isnanto, R
core   +1 more source

Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

Pharmaceutics, 2020
In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed.
Daan Van Hauwermeiren, Michiel Stock, Thomas De Beer, Ingmar Nopens   +3 more
doaj   +1 more source

Estimating Directed Phase-Amplitude Interactions from EEG Data through Kernel-Based Phase Transfer Entropy

Applied Sciences, 2021
Cross-frequency interactions, a form of oscillatory neural activity, are thought to play an essential role in the integration of distributed information in the brain.
Iván De La Pava Panche, Viviana Gómez-Orozco, Andrés Álvarez-Meza, David Cárdenas-Peña, Álvaro Orozco-Gutiérrez   +4 more
doaj   +1 more source

Revealing the distribution of transmembrane currents along the dendritic tree of a neuron from extracellular recordings

eLife, 2017
Revealing the current source distribution along the neuronal membrane is a key step on the way to understanding neural computations; however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain
Dorottya Cserpán, Domokos Meszéna, Lucia Wittner, Kinga Tóth, István Ulbert, Zoltán Somogyvári, Daniel K Wójcik   +6 more
doaj   +1 more source

Deep Kernel and Deep Learning for Genome-Based Prediction of Single Traits in Multienvironment Breeding Trials

Frontiers in Genetics, 2019
Deep learning (DL) is a promising method for genomic-enabled prediction. However, the implementation of DL is difficult because many hyperparameters (number of hidden layers, number of neurons, learning rate, number of epochs, batch size, etc.) need to ...
José Crossa, José Crossa, Johannes W.R. Martini, Daniel Gianola, Paulino Pérez-Rodríguez, Diego Jarquin, Philomin Juliana, Osval Montesinos-López, Jaime Cuevas   +8 more
doaj   +1 more source

FAILURE RATE REGRESSION MODEL BUILDING FROM AGGREGATED DATA USING KERNELBASED MACHINE LEARNING METHODS

Вісник Національного технічного університету "ХПÌ": Системний аналіз, управління та інформаційні технології, 2022
The problem of regression model building of equipment failure rate using datasets containing information on number of failures of recoverable systems and measurements of technological and operational factors affecting the reliability of production system
Olena Akhiiezer, Galyna Grinberg, Leonid Lyubchyk, Klym Yamkovyi   +3 more
doaj   +1 more source

UiO‐66 metal–organic frameworks in biomedicine: From structural tunability to bioimaging, photodiagnostics, and photodynamic cancer therapy

FEBS Open Bio, EarlyView.
UiO‐66(Zr) metal–organic frameworks are chemically stable, biocompatible, and highly tunable nanomaterials. Their modular structure enables controlled drug delivery, multimodal bioimaging, and light‐activated photodynamic therapy, supporting integrated diagnostic and therapeutic (theranostic) applications in cancer and biomedical research.
Veronika Huntošová, Grigorii Rakhalskii, Miroslav Almáši   +2 more
wiley   +1 more source