Efficient flexible characterization of quantum processors with nested error models
New Journal of Physics, 2021 We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its ...
Erik Nielsen +4 more
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Development and Evaluation of a Urinary Na/K Ratio Prediction Model: A Systematic Comparison from Attention-Based Deep Learning to Classical Ensemble Approaches [PDF]
BioengineeringThe urinary sodium-to-potassium (Na/K) ratio is a clinically established predictor of blood pressure and cardiovascular risk. This study aimed to develop and rigorously evaluate machine learning models for estimating the urinary Na/K ratio using four ...
Emi Yuda, Itaru Kaneko, Daisuke Hirahara
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Comparative evaluation of machine learning models for predicting Cimbex quadrimaculata population density across multiple problem formulations. [PDF]
PLoS ONEThe high variability and nonlinear relationships between environmental variables (such as temperature, relative humidity, and altitude) in ecological datasets prevent classical statistical models from obtaining accurate predictions.
Yunus Güral
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Chinese Nested Named Entity Recognition Algorithm Based on Segmentation Attention andBoundary-aware [PDF]
Jisuanji kexue, 2023 Chinese nested named entity recognition(CNNER) is a challenging task due to the absence of natural delimiters in Chinese and the complexity of the nested structure.In this paper,we propose a novel boundary-aware layered neural model(BLNM) with ...
ZHANG Rujia, DAI Lu, GUO Peng, WANG Bang
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Increasing cluster size asymptotics for nested error regression models [PDF]
Journal of Statistical Planning and Inference, 2022 15 ...
Lyu, Ziyang, Welsh, Alan
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Metamaterial Design with Nested-CNN and Prediction Improvement with Imputation
Applied Sciences, 2022 Metamaterials, which are not found in nature, are used to increase the performance of antennas with their extraordinary electromagnetic properties.
Erkan Kıymık, Ergun Erçelebi
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Heteroscedastic nested error regression models with variance functions [PDF]
Statistica Sinica, 2018 The nested error regression model is a useful tool for analyzing clustered (grouped) data, and is especially used in small area estimation. The classical nested error regression model assumes normality of random effects and error terms, and homoscedastic variances.
Shonosuke Sugasawa, Tatsuya Kubokawa
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Nested Named Entity Recognition via an Independent-Layered Pretrained Model
IEEE Access, 2021 When an entity contains one or more entities, these particular entities are referred to as nested entities. The Layered BiLSTM-CRF model can use multiple BiLSTM layers to identify nested entities. However, as the number of layers increases, the number of
Liruizhi Jia +4 more
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Hybrid Look-Up-Tables Based Behavioral Model for Dynamic Nonlinear Power Amplifiers
IEEE Access, 2020 A new look-up table based behavioral model for dynamic nonlinear power amplifiers is proposed. This model labelled as hybrid look-up tables model is based on the combination of a memoryless look-up table sub-model and a nested look-up tables one.
Ahmad I. Dalbah +2 more
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Buildings, 2023 This paper proposes a Bayesian RC-frame finite element model updating (FEMU) and damage state estimation approach using the nonlinear acceleration time history based on nested sampling.
Kunyang Wang +2 more
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