An Autotuning Hybrid Method with Bayesian Optimization for Road Edge Extraction in Highway Systems from Point Clouds by Jingxu Chen, Qiru Cao, Mingzhuang Hua, Jinyang Liu, Jie Ma, Di Wang, Aoxiang Liu

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Artificial intelligence-based Bayesian optimization and transformer model for tennis motion recognition by Shaowei Shi, Kun Huang

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Optimal spectroscopic measurement design: Bayesian framework for rational data acquisition by Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono

“…In this work, we developed a method for extracting prior information from a standard spectral database and incorporating it into the Bayesian experimental design framework to determine the optimal measurement points automatically. …”
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Deep learning with Bayesian Hyperparameter Optimization for Precise Electrocardiogram Signals Delineation by Annisa Darmawahyuni, Winda Kurnia Sari, Nurul Afifah, Siti Nurmaini, Jordan Marcelino, Rendy Isdwanta

“…In this study, we propose a deep learning approach combined with Bayesian Hyperparameter Optimization (BHO) for hyperparameter tuning to delineate the ECG signal. …”
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Bayesian optimization of radical polymerization reactions in a flow synthesis system by Shogo Takasuka, Sho Ito, Shunto Oikawa, Yosuke Harashima, Tomoaki Takayama, Aniruddha Nag, Araki Wakiuchi, Tsuyoshi Ando, Tetsunori Sugawara, Miho Hatanaka, Tomoyuki Miyao, Takamitsu Matsubara, Yu-Ya Ohnishi, Hiroharu Ajiro, Mikiya Fujii

“…Subsequent Bayesian Optimization (BO) trial, using 40 points per cycle, identified several sets of processing conditions that could achieve the desired copolymer composition, accompanied by variations in other physical properties. …”
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Optimizing a Bayesian Method for Estimating the Hurst Exponent in Behavioral Sciences by Madhur Mangalam, Taylor J. Wilson, Joel H. Sommerfeld, Aaron D. Likens

“…The present results allow the reader to make judgments to optimize the Bayesian estimation of the Hurst exponent for real-time applications.…”
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Anatomical Plausibility in Deformable Image Registration Using Bayesian Optimization for Brain MRI Analysis by Mauricio Castaño-Aguirre, Hernán Felipe García, David Cárdenas-Peña, Gloria Liliana Porras-Hurtado, Álvaro Ángel Orozco-Gutiérrez

“…This paper proposes a novel framework that uses Bayesian optimization to address these challenges, focusing on registering 3D point clouds that represent brain structures. …”
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Multi-objective Bayesian optimization of eco-friendly gas mixtures for resistive plate chambers by Pit Bechtold, Dario Stocco, Christian M Franck

“…The proposed framework is built upon multi-objective Bayesian optimization (BO) with Pareto front prediction and per-point noise implementation. …”
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Structural Disorder by Octahedral Tilting in Inorganic Halide Perovskites: New Insight with Bayesian Optimization by Jingrui Li, Fang Pan, Guo‐Xu Zhang, Zenghui Liu, Hua Dong, Dawei Wang, Zhuangde Jiang, Wei Ren, Zuo‐Guang Ye, Milica Todorović, Patrick Rinke

“…The rapid convergence of the PES with about 200 DFT data points in 3D searches demonstrates the power of active learning and strategic sampling with Bayesian optimization. …”
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Benchmarking Diffusion Annealing-Based Bayesian Inverse Problem Solvers by Evan Scope Crafts, Umberto Villa

“…In recent years, the ascendance of diffusion modeling as a state-of-the-art generative modeling approach has spurred significant interest in their use as priors in Bayesian inverse problems. However, it is unclear how to optimally integrate a diffusion model trained on the prior distribution with a given likelihood function to obtain posterior samples. …”
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High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization With Sparse Training Point by Haiqi Zhang, Jiahe Cui, Lihui Feng, Aiying Yang, Huichao Lv, Bo Lin, Heqing Huang

“…In this letter, we propose an indoor visible light positioning technique that combines deep neural network based on the Bayesian Regularization (BR-DNN) with sparse diagonal training data set. …”
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Reinforcement Learning-Based Augmentation of Data Collection for Bayesian Optimization Towards Radiation Survey and Source Localization by Jeremy Marquardt, Leonard Lucas, Stylianos Chatzidakis

“…Safer and more efficient characterization of radioactive environments requires exploring intelligently, utilizing robotic systems which use smart strategies and physics-based statistical models. Bayesian Optimization (BO) provides one such statistical framework to explainably find the global maximum within noisy contexts while also minimizing the number of trials. …”
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Leveraging Bayesian optimization and multilayer artificial neural network (MLANN) for fault prediction in oil-immersed transformers by Elahe Moradi

“…The proposed multilayer artificial neural network model, optimized using the Bayesian optimization method, achieved an outstanding accuracy of 97.99 %, pointedly outperforming benchmark machine learning classifiers. …”
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A Cost of Misclassification Adjustment Approach for Estimating Optimal Cut-Off Point for Classification by O.-A. Ampomah, R. Minkah, G. Kallah-Dagadu, E. N. N. Nortey

“…By doing so, we can systematically shift the cut-off point within its measurement range till the optimal point is obtained. …”
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Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…This article proposed a comprehensive health prediction model for hydroelectric equipment based on the multimeasurement point output, which realized real-time monitoring and prediction of the health state of hydroelectric equipment, optimized maintenance strategies, and reduced maintenance difficulty. …”
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Impact of transitioning from antibiotic use to antibiotic-free practices on broiler dead-on-arrival rates: A bayesian structural time series approach by Panneepa Sivapirunthep, Pranee Pirompud, Veerasak Punyapornwithaya, Supitchaya Srisawang, Chalita Jainonthee, Chanporn Chaosap

“…Seasonal fluctuations were observed, with %DOA peaking between February and April and reaching its lowest point in October. Changepoint analysis identified six significant shifts in %DOA, with the highest values occurring in 2015. …”
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Dynamic selection of optimal tunnel convergence prediction model for a probabilistic deformation prediction by Peng ZENG, Zhiqiang ZHANG, Tianbin LI, Hao Tang, Zulong YAN, Lubo MENG

“…Methods To address this, this study introduces a dynamic prediction model for tunnel convergence based on continuous Bayesian updating and an optimal model selection strategy. …”
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Bayesian Denoising Algorithm for Low SNR Photon-Counting Lidar Data via Probabilistic Parameter Optimization Based on Signal and Noise Distribution by Qi Liu, Jian Yang, Yue Ma, Wenbo Yu, Qijin Han, Zhibiao Zhou, Song Li

“…This study proposes an adaptive Bayesian denoising algorithm integrating minimum spanning tree (MST) -based slope estimation and probabilistic parameter optimization. …”
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Parallel Bayesian Optimization of Thermophysical Properties of Low Thermal Conductivity Materials Using the Transient Plane Source Method in the Body-Fitted Coordinate by Huijuan Su, Jianye Kang, Yan Li, Mingxin Lyu, Yanhua Lai, Zhen Dong

“…A body-fitted coordinate system is proposed to transform the unstructured grid structure to improve the speed of solving the heat transfer direct problem of the winding probe. A parallel Bayesian optimization algorithm based on a multi-objective hybrid strategy (MHS) is proposed based on an inverse problem. …”
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Identification of global main cable line shape parameters of suspension bridges based on local 3D point cloud by Yurui Li, Danhui Dan, Ruiyang Pan

“…Additionally, the Random Sample Consensus (RANSAC) algorithm, the ordinary least squares, and center-of-mass calibration are applied to identify and optimize the geometric parameters of the cross-section point cloud of the main cable. …”
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