Abstract: Bayesian inversion is capable of integrating seismic data, well-log data, and geological data to obtain a posterior probability distribution function (PPDF) of elastic parameters. Due to the ...
Predicting the response of cell lines to characteristic drugs based on multi-omics gene information has become the core problem of precision oncology. At present, drug response prediction using ...
Abstract: Acoustic impedance (AI) is an important parameter for seismic reservoir characterization. Traditional algorithms can obtain AI whereas the resolution is open to improvement. Single-channel ...
Data assimilation (DA) is used to obtain the best states and their uncertainty of the Earth system by incorporating possible states measured through numerical-model-based forecasting and observations ...
Diagnosis of shockable rhythms leading to defibrillation remains integral to improving out‐of‐hospital cardiac arrest outcomes. New machine learning techniques have emerged to diagnose arrhythmias on ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. As a supervised machine learning algorithm, conditional random fields are mainly used ...
Advanced algorithms are required to reveal the complex relations between neural and behavioral data. In this study, forelimb electromyography (EMG) signals were reconstructed from multi-unit neural ...
Fast-scan cyclic voltammetry permits robust subsecond measurements of in vivo neurotransmitter dynamics, resulting in its established use in elucidating these species’ roles in the actions of behaving ...
Five ILSVRC-2010 test images in the first column. Remaining columns show the training images that produce feature vectors in the last hidden layer with the smallest Euclidean distance from the feature ...
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