Humans adapt rationally to approximate estimates of uncertainty by Erdem Pulcu, Michael Browning

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Understanding climate-sensitive tick development and diapause with a structured population model by Kamil Erguler, Anastasios Saratsis, Gerhard Dobler, Lidia Chitimia-Dobler

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Spatio-temporal pattern and risk factors of HIV/AIDS prevalence in Zhejiang, China, from 2005 to 2022 using R-INLA by Yifan Tang, Yifan Chen, Jinglei Zheng, Wei Cheng, Yurong Jing, Yushu Zhang, Chengliang Chai, Chengxiu Ling, Ying Wang

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Nonlinear AVA Inversion Based on a Novel Quadratic Approximation for Fluid Discrimination by Lin Zhou, Xingye Liu, Tianchun Yang, Jianping Liao, Mingfeng Zhu, Gan Zhang

“…Therefore, inversion methods based on linear approximations will seriously influence the nonuniqueness and uncertainty of inversion results. …”
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Study on the Probability of Meteorological-to-Hydrological Drought Propagation Based on a Bayesian Network by Xiangyang Zhang, Huiliang Wang, Zhilei Yu, Dengming Yan, Ruxue Liu, Simin Liu, Yujia Zhu, Yifan Chen, Zening Wu

“…This study constructed a Standardized Temperature Index (STI) and, combined with time-series datasets of standardized indices of precipitation and runoff (SPI and SRI), based on Bayesian network principles, analyzed the probabilistic characteristics of drought propagation from meteorology to hydrology due to the influence of single or dual factors in the Yiluo River Basin (1961–2020). …”
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Novel cooperative global spectrum sensing algorithm based on variational Bayesian inference by Ming WU, Tie-cheng SONG, Jing HU, Lian-feng SHEN

“…Then, an estimator of mod-el coefficient vector was designed by utilizing the th of variational Bayesian inference (VBI). Simulation results show that the proposed approximate model has good accuracy, and the corresponding estimation algorithm of model coefficient vector has good convergence and stability. …”
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Mapping and understanding the regional farmland SOC distribution in southern China using a Bayesian spatial model by Bifeng Hu, Yibo Geng, Hanjie Ni, Zhou Shi, Zheng Wang, Nan Wang, Jipeng Luo, Modian Xie, Qian Zou, Thomas Optiz, Hongyi Li

“…To fill these gaps, here we use a Bayesian spatial model termed Integrated Nested Laplace Approximation with the Stochastic Partial Differential Equation (INLA-SPDE) to produce the fine scale SOC map in the farmland of Jiangxi Province, south China based on an extensive soil survey dataset (n = 16,050). …”
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Spatial disparities of antenatal care utilization among pregnant women in sub-Saharan Africa—Bayesian geo-additive modelling approach by Denekew Bitew Belay, Denekew Bitew Belay, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Haile Mekonnen Fenta, Nigussie Adam Birhan, Najmeh Nakhaei Rad, Ding-Geng Chen, Ding-Geng Chen

“…Despite its importance, significant disparities in ANC access and utilization exist across sub-Saharan Africa (SSA), influenced by various socioeconomic, geographical, and systemic factors. …”
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The Role of Consumer Characteristics and Marketing Mix on the Waste of Agricultural Products by M. Mahmoudi, H. Mohammadi, A. Karbasi

“…Therefore, the multilevel Bayesian model was selected as the most appropriate tool, as discussed in the following section on the modeling methodology.   …”
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Online Learning to Cache and Recommend in the Next Generation Cellular Networks by Krishnendu S. Tharakan, B. N. Bharath, Vimal Bhatia

“…Using this result, we show that the approximate regret achieved by the genie aided <monospace>Point estimation</monospace> approach is <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(T^{2/3} \sqrt {\log T})$ </tex-math></inline-formula> while the <monospace>Bayesian estimation</monospace> method achieves a much better scaling of <inline-formula> <tex-math notation="LaTeX">$\mathcal {O}(\sqrt {T})$ </tex-math></inline-formula>. …”
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The Optimal Padé Polynomial for Reconstruction of Luminosity Distance Based on 10-fold Cross Validation by Bo Yu, Wen-Hu Liu, Xiaofeng Yang, Tong-Jie Zhang, Yanke Tang

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Spatiotemporal Bayes model for estimating the number of hotspots as an indicator of forest and land fires in Kalimantan Island, Indonesia by FADILLAH ROHIMAHASTUTI, ANIK DJURAIDAH, HARI WIJAYANTO

“…This research aims to predict the number of hotspot spatially and temporally in the next month on Kalimantan Island and analyze the influence of local climate on hotspot events. The Bayesian Conditional Autoregressive method with Integrated Nested Laplace Approximation and optimal weight selection using Getis-Ord G are used to increase prediction accuracy. …”
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Evaluation of the effectiveness of rehabilitation for diabetic foot syndrome by T. H. Bakaliuk, N. R. Маkarchuk, Kh. M. Seniuk, H. O. Stelmakh, A. S. Sverstiuk

“…Using the Bayesian formula, the probability of complete ulcer healing in the CG was calculated, that was 0.3 compared to the MG – 0.06, indicating greater treatment effectiveness with the inclusion of additional non-drug rehabilitation methods. …”
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Augmenting Naïve Bayes Classifiers with <i>k</i>-Tree Topology by Fereshteh R. Dastjerdi, Liming Cai

“…Therefore, this algorithm can be employed to ensure efficient approximation of Bayesian networks with <i>k</i>-tree augmented Naïve Bayesian classifiers of the guaranteed minimum loss of information.…”
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Climate influence on the early human occupation of South America during the late Pleistocene by L. Becerra-Valdivia

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A flexible statistical distribution for capturing complex patterns in industrial data by Ehab M. Almetwally, Amal S. Hassan, Mohamed Kayid, Arne Johannssen, Mohammed Elgarhy

“…To estimate the model parameters, both frequentist and Bayesian techniques are implemented. The bootstrap approach, the normal approximation method, and Bayesian credible intervals are some of the techniques employed to build confidence intervals. …”
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Distributionally Robust Variational Quantum Algorithms With Shifted Noise by Zichang He, Bo Peng, Yuri Alexeev, Zheng Zhang

“…We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. …”
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In and out: factors influencing two decades of straying and homing by Pacific salmon within the Columbia River basin by Peter A. H. Westley, Andrew H. Dittman, Benjamin W. Nelson, Morgan H. Bond, Molly Payne, Thomas P. Quinn

“…In addition to patch size and spatial isolation, habitat quality can also influence attractiveness of patches to dispersing individuals. …”
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Simulation-based inference of surface accumulation and basal melt rates of an Antarctic ice shelf from isochronal layers by Guy Moss, Vjeran Višnjević, Olaf Eisen, Falk M. Oraschewski, Cornelius Schröder, Jakob H. Macke, Reinhard Drews

“…We solve the inverse problem using simulation-based inference (SBI). SBI performs Bayesian inference by training neural networks on simulations of the forward model to approximate the posterior distribution, therefore also quantifying uncertainties over the inferred parameters. …”
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Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation by Xiang Yu, Guodong Fan, Jinjiang Li

“…Nitrate is a critical limiting nutrient that significantly influences marine primary productivity and carbon sequestration. …”
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