Results 111 to 120 of about 6,870,757 (231)
Advanced Intelligent Systems, EarlyView.A training‐free two‐stage BO–RL framework extracts compact model parameters for a‐IGZO TFTs, reaching BO‐level fitting quality at a constant per‐simulation optimization cost. Bayesian optimization performs exploration and provides an optimized starting point.
Seunghyun Son +4 more
wiley +1 more source
, 2008 This one page article, created by Statistics Canada, describes the meaning behind random sampling error. It points our the relationship of the random sampling error with the sample size, population size, variability of the characteristic, sampling plan,
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Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Incorporating a Shortened Long-Term Effectiveness End Point Into Catheter Ablation Trials: Statistical Properties and Implications. [PDF]
Circ Arrhythm ElectrophysiolAndrade JG +3 more
europepmc +1 more source
Well-Posedness of Measurement Error Models for Self-Reported Data [PDF]
It is widely admitted that the inverse problem of estimating the distribution of a latent variable X* from an observed sample of X, a contaminated measurement of X*, is ill-posed.
Yonghong An, Yingyao Hu
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Bronchoscope Tip Localization With Learned Airway Constraints and an Open Source Simulator
Advanced Intelligent Systems, EarlyView.BronchoLoc addresses feature‐poor bronchoscopic imaging by combining monocular video with a preoperative CT graph to estimate 3D camera location. A local tracker identifies candidate branches, while a sequence‐aware global module refines the trajectory. Demonstrating sub‐centimeter accuracy across synthetic and phantom datasets, this framework advances
Emanuele Nicotra +7 more
wiley +1 more source
A Bayesian Adaptive Design for Assessing Treatment Effect Consistency in Bridging Studies. [PDF]
Stat MedHe X, Zhao D, Teng Z, Liu H, Yuan Y.
europepmc +1 more source
On Network-Error Correcting Convolutional Codes under the BSC Edge Error Model
, 2010 Convolutional network-error correcting codes (CNECCs) are known to provide error correcting capability in acyclic instantaneous networks within the network coding paradigm under small field size conditions. In this work, we investigate the performance of
Sundar B, Rajan, Prasad, K
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Vertical NAND Flash Memory‐Based Bayesian Neural Networks With Intrinsic Gaussian Weight Sampling
Advanced Intelligent Systems, EarlyView.Commercial vertical NAND flash memory supports Bayesian neural networks by using paired cells to produce bell‐shaped weight distributions. Read voltage controls their spread without additional memory cells or changes to the array structure. Simulations based on device measurements demonstrate improved uncertainty estimation and accuracy gains of up to ...
Sung‐Ho Park +8 more
wiley +1 more source
ORDER-STATISTICS MINIMUM ERROR RATE DETECTOR
, 2014 International audienceA new methodology for random signal detection, in presenceof closely spaced interfering signals, is introduced, namelythe Order-Statistics Minimum Error Rate (OS-MER) detector.The latter is based on the minimization of the error ...
Belouchrani, Adel +3 more
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