Results 131 to 140 of about 67,030 (311)
Advanced Intelligent Discovery, EarlyView.Matrix‐assisted laser desorption/ionization imaging‐based identification of reliable small molecule markers across heterogeneous glioblastoma cohorts is challenging with intensity‐only methods. We present spatially informed feature selection (SIFS), a spatially informed framework that prioritizes molecules consistently colocalizing with histopathology.
Shad A. Mohammed +15 more
wiley +1 more source
A Nonparametric Model of Frontiers [PDF]
In this paper we propose a nonparametric regression frontier model that assumes no specific parametric family of densities for the unobserved stochastic component that represents efficiency in the model.
Carlos Martins-FIlho, Feng Yao
core
Human‐in‐the‐Loop Object Segmentation for 3D Gaussian Splatting via Finger‐based VR Interface
Advanced Intelligent Systems, EarlyView.This study introduces a human‐in‐the‐loop segmentation framework for 3D Gaussian Splatting that integrates real‐time optimization with intuitive VR‐based finger prompting. Compared with existing automatic, learning‐based methods, it achieves significantly higher accuracy and reduced segmentation time.
Yongseok Lee +5 more
wiley +1 more source
Nonparametric Estimation of Risk-Neutral Densities [PDF]
This chapter deals with nonparametric estimation of the risk neutral density. We present three different approaches which do not require parametric functional assumptions on the underlying asset price dynamics nor on the distributional form of the risk ...
Wolfgang Karl Härdle +2 more
core
Nonparametric serial interval estimation with uniform mixtures.
PLoS Computational BiologyThe serial interval of an infectious disease is a key instrument to understand transmission dynamics. Estimation of the serial interval distribution from illness onset data extracted from transmission pairs is challenging due to the presence of censoring
Oswaldo Gressani, Niel Hens
doaj +1 more source
pyrichlet: A Python Package for Density Estimation and Clustering Using Gaussian Mixture Models
Journal of Statistical SoftwareBayesian nonparametric models have proven to be successful tools for clustering and density estimation. While there exists a nourished ecosystem of implementations in R, for Python there are only a few. Here we develop a Python package called pyrichlet,
Fidel Selva +2 more
doaj +1 more source
Advanced Intelligent Systems, EarlyView.Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal +6 more
wiley +1 more source
Nonparametric confidence bands in deconvolution density estimation [PDF]
Uniform confidence bands for densities f via nonparametric kernel estimates were first constructed by Bickel and Rosenblatt [Ann. Statist. 1, 1071.1095].
Bissantz, Nicolai +3 more
core
MathematicsThe most widely used method for trend estimation in economics is the Hodrick-Prescott (HP) filter. The HP filter has various disadvantages, such as the arbitrary, frequency-dependent choice of the smoothing parameter λ, boundary problems, and difficult ...
Marlon Fritz, Thomas Gries, Yuanhua Feng
doaj +1 more source
Nonparametric Estimation of Population Average Dose-Response Curves using Entropy Balancing Weights for Continuous Exposures. [PDF]
Health Serv Outcomes Res Methodol, 2021 Vegetabile BG +5 more
europepmc +1 more source