Results 1 to 10 of about 638,211 (165)
A nonparametric Bayesian continual reassessment method in single-agent dose-finding studies
BMC Medical Research Methodology, 2018 Background The main purpose of dose-finding studies in Phase I trial is to estimate maximum tolerated dose (MTD), which is the maximum test dose that can be assigned with an acceptable level of toxicity.
Niansheng Tang, Songjian Wang, Gen Ye
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Mathematics, 2022 This paper is devoted to proposing a modified conjugate residual method for solving the generalized coupled Sylvester tensor equations. To further improve its convergence rate, we derive a preconditioned modified conjugate residual method based on the ...
Tao Li, Qing-Wen Wang, Xin-Fang Zhang
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Updated distribution maps of predominant Culex mosquitoes across the Americas
Parasites & Vectors, 2021 Background Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s.
Morgan E. Gorris +8 more
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Estimating effective reproduction number revisited
Infectious Disease Modelling, 2023 Accurately estimating the effective reproduction number is crucial for characterizing the transmissibility of infectious diseases to optimize interventions and responses during epidemic outbreaks. In this study, we improve the estimation of the effective
Shinsuke Koyama
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Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A Review
Entropy, 2023 In this study, we present a thorough comparison of the performance of four different bootstrap methods for assessing the significance of causal analysis in time series data. For this purpose, multivariate simulated data are generated by a linear feedback
Fumikazu Miwakeichi, Andreas Galka
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Spatio-Temporal Analysis of Urban Heatwaves Using Tukey g-and-h Random Field Models
IEEE Access, 2021 Real-time heatwave risk management with fine-grained spatial resolution is important for analysis of urban heat island (UHI) effects and local heatwaves.
Daisuke Murakami +3 more
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Adaptive Differential Privacy Cox-MLP Model Based on Federated Learning
MathematicsIn the data-driven healthcare sector, balancing privacy protection and model performance is critical. This paper enhances accuracy and reliability in survival analysis by integrating differential privacy, deep learning, and the Cox proportional hazards ...
Jie Niu +6 more
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adabmDCA: adaptive Boltzmann machine learning for biological sequences
BMC Bioinformatics, 2021 Background Boltzmann machines are energy-based models that have been shown to provide an accurate statistical description of domains of evolutionary-related protein and RNA families.
Anna Paola Muntoni +3 more
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Music Genre and Emotion Recognition Using Gaussian Processes
IEEE Access, 2014 Gaussian Processes (GPs) are Bayesian nonparametric models that are becoming more and more popular for their superior capabilities to capture highly nonlinear data relationships in various tasks, such as dimensionality reduction, time series analysis ...
Konstantin Markov, Tomoko Matsui
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Federated Learning Based on Kernel Local Differential Privacy and Low Gradient Sampling
IEEE AccessFederated learning that is an approach to addressing the “data silo” problem in a collaborative fashion may face the risk of data leakage in real-world contexts.
Yi Chen, Dan Chen, Niansheng Tang
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