Diabetes prediction using optimized machine learning algorithms with grid search and Bayesian optimization. by Muhammad Rizwan Khurshid (20613973)

“…<p>Diabetes prediction using optimized machine learning algorithms with grid search and Bayesian optimization.…”

Bayesian Optimization Methods for Nonlinear Model Calibration by Montana N. Carlozo (22175927)

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Bayesian Optimization Methods for Nonlinear Model Calibration by Montana N. Carlozo (22175927)

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Bayesian Optimization Methods for Nonlinear Model Calibration by Montana N. Carlozo (22175927)

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Bayesian Optimization Methods for Nonlinear Model Calibration by Montana N. Carlozo (22175927)

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Bayesian optimization results of key hyperparameters. by Hang Zhao (143592)

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Optimization process of BO algorithm. by Hoa Thi Trinh (20347834)

“…The study used the largest database of RC walls to date, consisting of 1057 samples with various cross-sectional shapes. Bayesian optimization (BO) algorithms, including BO—Gaussian Process, BO—Random Forest, and Random Search methods, were used to refine the XGBoost model architecture. …”

Physics-Informed Bayesian Optimization for Conformational Ensemble Augmentation by Ivan A. Bespalov (21491561)

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Physics-Informed Bayesian Optimization for Conformational Ensemble Augmentation by Ivan A. Bespalov (21491561)

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Physics-Informed Bayesian Optimization for Conformational Ensemble Augmentation by Ivan A. Bespalov (21491561)

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Comparison of different optimization algorithms. by Hang Zhao (143592)

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G R code algorithm. by R. Sakthivel (2589547)

“…The algorithm was developed and coded in Verilog and simulated using Modelsim. …”

Code and data. by Shangyang Jin (21772466)

Accelerated Discovery of Solid-State Electrolytes Using Bayesian Optimization by Sherif Abdulkader Tawfik (3820180)

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The Pseudo-Code of the IRBMO Algorithm. by Chenyi Zhu (9383370)

Maple code for algorithm 3. by Peter Thompson (165468)

Data and code availability: Machine Learning on systematically curated data reveals key determinants of magnetic hyperthermia performance by Edgar Vega (21981590)

“…Twelve machine learning models were evaluated and refined using Bayesian hyperparameter optimization. The CatBoost algorithm emerged as the most effective model, achieving the lowest mean absolute error (20.92 W/g) and root mean squared error (39.41 W/g), along with a high coefficient of determination (R² = 0.98). …”

BeeSwarm-MH Sampling for Bayesian Inference of GL Equation Parameters by Lipu Zhang (21475718)

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code&data by Liyuan Liu (18298084)

The metro zone algorithm pseudo-code. by Sarah Alhumoud (22258183)