Results 91 to 100 of about 5,652,238 (291)

Supervised Machine Learning with Control Variates for American Option Pricing

open access: yesFoundations of Computing and Decision Sciences, 2018
In this paper, we make use of a Bayesian (supervised learning) approach in pricing American options via Monte Carlo simulations. We first present Gaussian process regression (Kriging) approach for American options pricing and compare its performance in ...
Mu Gang   +3 more
doaj   +1 more source

Sex‐Stratified Association of Regional Dopamine Transporter Binding With Disease Progression in Amyotrophic Lateral Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To clarify the clinical relevance of dopamine transporter single‐photon emission computed tomography (DAT‐SPECT) abnormalities in amyotrophic lateral sclerosis (ALS), with a prespecified focus on sex‐stratified associations with disease progression and short‐term prognosis.
Tomoya Kawazoe   +7 more
wiley   +1 more source

Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias   +3 more
wiley   +1 more source

Absolute Moments of Generalized Hyperbolic Distributions and Approximate Scaling of Normal Inverse Gaussian Lévy-Processes [PDF]

open access: yes, 2004
Expressions for (absolute) moments of generalized hyperbolic (GH) and normal inverse Gaussian (NIG) laws are given in terms of moments of the corresponding symmetric laws.
Barndorff-Nielsen, Ole Eiler   +1 more
core   +1 more source

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay   +15 more
wiley   +1 more source

Comparative Analysis of Choroid Plexus Volume Between MOG Antibody Associated Disease and Multiple Sclerosis

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Choroid plexus volume (CPV) has been proposed as a neuro‐immunological marker of multiple sclerosis (MS), but its relevance in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD) remains uncertain. We analyzed CPV in 43 individuals with MOGAD, 48 with MS, and 44 healthy controls using a Bayesian Gaussian mixture modeling ...
Jae‐Won Hyun   +4 more
wiley   +1 more source

White Matter and Perivascular Imaging Changes in Alzheimer's Disease and Cerebral Amyloid Angiopathy

open access: yesAnnals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peak‐width of skeletonized mean diffusivity (PSMD) and diffusion tensor imaging–analysis along the perivascular space (DTI‐ALPS), reflecting white matter integrity and glymphatic function, are altered in Alzheimer's disease (AD).
Debina Laishram   +3 more
wiley   +1 more source

Characteristic function estimation of non-Gaussian Ornstein-Uhlenbeck processes. [PDF]

open access: yes
Continuous non-Gaussian stationary processes of the OU-type are becoming increasingly popular given their flexibility in modelling stylized features of financial series such as asymmetry, heavy tails and jumps.
Emanuele Taufer
core  

Gaussian processes for inferring parton distributions

open access: yesJournal of High Energy Physics
The extraction of parton distribution functions (PDFs) from experimental or lattice QCD data is an ill-posed inverse problem, where regularization strongly impacts both systematic uncertainties and the reliability of the results.
Yamil Cahuana Medrano   +5 more
doaj   +1 more source

Experimental Evaluation of Machine Learning Methods for Robust Received Signal Strength-Based Visible Light Positioning

open access: yesSensors, 2020
In this work, the use of Machine Learning methods for robust Received Signal Strength (RSS)-based Visible Light Positioning (VLP) is experimentally evaluated.
Willem Raes   +4 more
doaj   +1 more source

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