Results 61 to 70 of about 291,981 (317)
Spatial patterns in population trends, particularly those at fine geographic scales, can help better understand the factors driving population change in North American birds.
Adam C Smith +11 more
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Gaussian Process for Trajectories
The Gaussian process is a powerful and flexible technique for interpolating spatiotemporal data, especially with its ability to capture complex trends and uncertainty from the input signal. This chapter describes Gaussian processes as an interpolation technique for geospatial trajectories.
Nguyen, Kien +2 more
openaire +2 more sources
ABSTRACT Objectives To evaluate the utility of cerebrospinal fluid (CSF) biomarkers—matrix metalloproteinase‐9 (MMP‐9), tissue inhibitor of metalloproteinases‐1 (TIMP‐1), the MMP‐9/TIMP‐1 ratio, and osteopontin (OPN)—as indicators of blood–brain barrier (BBB) integrity and disease activity in people with relapsing–remitting multiple sclerosis (pwMS ...
Ivan Pavlovic +6 more
wiley +1 more source
Workflow of the parameter optimization process for ITSC fault detection, applying Differential Evolution optimization and the Smooth Pseudo Wigner‐Ville Distribution for signal processing. The optimized parameters are then used in the failure identification pipeline, which combines the signal processing with a YOLO‐based architecture for fault severity
Rafael Martini Silva +4 more
wiley +1 more source
Landslide susceptibility mapping using various soft computing techniques (Case study: A part of Haraz Watershed) [PDF]
IntroductionA landslide is one of the mass movements on the top surface of the earth. Landslides have resulted in notable injury and damage to human life and destroyed infrastructure and property.
Alireza Sepahvand, Nasrin Beiranvand
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Gaussian Processes for Regression [PDF]
The Bayesian analysis of neural networks is difficult because a sim ple prior over weights implies a complex prior distribution over functions. In this paper we investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian anal ysis for fixed values of hyperparameters to be carried out exactly using matrix ...
Williams, Christopher, Rasmussen, Carl
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Regression with Gaussian Processes [PDF]
The Bayesian analysis of neural networks is difficult because the prior over functions has a complex form, leading to implementations that either make approximations or use Monte Carlo integration techniques. In this paper I investigate the use of Gaussian process priors over functions, which permit the predictive Bayesian analysis to be carried out ...
openaire +2 more sources
Monotonic Gaussian Process Flows [PDF]
Proceedings of the 23nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2020 (14 pages)
Ustyuzhaninov, I +3 more
openaire +4 more sources
Infrared (IR) light evokes distinct calcium and water transport responses in astrocytes, depending on stimulation duration and protocol. This study uses widefield imaging and pharmacology to reveal differential engagement of astroglial signaling pathways.
Wilson R. Adams +7 more
wiley +1 more source
Revisiting statefinder via Gaussian process
The statefinder diagnostic is useful to discriminate dark energy models. In this paper, under the minimum assumption of a spatially flat Friedmann–Lemaître–Robertson–Walker Universe, we reconstruct the statefinder pair $$\{r(z),s(z)\}$$ { r ( z ) , s ( z
Zhihua Feng, Lixin Xu
doaj +1 more source

