Results 61 to 70 of about 8,348,933 (325)
The NOSE Platform®: A Real-Time Solution to Forecast & Monitor Nuisance Odours
Chemical Engineering Transactions, 2012 In recent years, the public’s awareness and response to nuisance odours have risen markedly. Accordingly, integration of industrial sites, such as wastewater treatment plants and solid waste treatment facilities, within their local environment represents
A. Givelet +3 more
doaj +1 more source
The DNNLikelihood: enhancing likelihood distribution with Deep Learning
European Physical Journal C: Particles and Fields, 2020 We introduce the DNNLikelihood, a novel framework to easily encode, through deep neural networks (DNN), the full experimental information contained in complicated likelihood functions (LFs).
Andrea Coccaro +3 more
doaj +1 more source
Sensitivity of galaxy cluster dark energy constraints to halo modeling uncertainties
, 2010 We perform a sensitivity study of dark energy constraints from galaxy cluster surveys to uncertainties in the halo mass function, bias and the mass-observable relation.
August E. Evrard +2 more
core +1 more source
Journal of Vision, 2013 Adaptive testing methods serve to maximize the information gained regarding the values of the parameters of a psychometric function (PF). Such methods typically target only one or two ("threshold" and "slope") of the PF's four parameters while assuming ...
N. Prins
semanticscholar +1 more source
PAIR: Reconstructing Single‐Cell Open‐Chromatin Landscapes for Transcription Factor Regulome Mapping
Advanced Science, EarlyView.scATAC‐seq analysis is often constrained by limited sequencing depth, extreme sparsity, and pervasive technical missingness. PAIR is a probabilistic framework that restores scATAC‐seq accessibility profiles by directly modeling the native cell–peak bipartite structure of chromatin accessibility.
Yanchi Su +7 more
wiley +1 more source
The Agreement between the Generalized p Value and Bayesian Evidence in the One-Sided Testing Problem
International Journal of Mathematics and Mathematical Sciences, 2016 In the problem of testing one-sided hypotheses, a frequentist may measure evidence against the null hypothesis by the p value, while a Bayesian may measure it by the posterior probability that the null hypothesis is true.
Yuliang Yin, Bingbing Wang
doaj +1 more source
Distinct Biotypes of Visual Perception in Major Depressive Disorder
Advanced Science, EarlyView.In a discover dataset (272 acute MDD patients), this work identifies a novel depression biotype characterized by impaired visual motion perception, using machine learning clustering. An independent dataset confirms the robustness of this biotype through cross‐validation and demonstrates its generalizability.
Zhuoran Cai +13 more
wiley +1 more source
Ordering Algorithms and Confidence Intervals in the Presence of Nuisance Parameters
, 2005 We discuss some issues arising in the evaluation of confidence intervals in the presence of nuisance parameters (systematic uncertainties) by means of direct Neyman construction in multi-dimensional space.
Punzi, Giovanni
core +2 more sources
Advanced Intelligent Systems, EarlyView.A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley +1 more source
Approximated Information Analysis in Bayesian Inference
Entropy, 2015 In models with nuisance parameters, Bayesian procedures based on Markov Chain Monte Carlo (MCMC) methods have been developed to approximate the posterior distribution of the parameter of interest.
Jung In Seo, Yongku Kim
doaj +1 more source