Results 191 to 200 of about 151,967 (341)

Grid search hyperparameter tuning in additive manufacturing processes

Manufacturing Letters, 2023
Michael Ogunsanya, Joan C. Isichei, Salil S. Desai   +2 more
semanticscholar   +1 more source

Physics‐Guided Descriptors Enable Data‐Efficient Prediction of Battery Coulombic Efficiency

Advanced Science, EarlyView.
This work integrates multiscale simulations with data‐driven approaches to predict Coulombic efficiency (CE). Multiscale simulations of battery systems are performed to extract Physics‐Guided descriptors and construct a dataset. Machine learning models trained on this dataset are then subjected to interpretable analysis to identify the most influential
Qintao Sun, Xuewei Gu, Yulin Jie, Hao Yang, Shuhong Jiao, Chao Tang, Yangping Sheng, Yuhao Lu, Ruiguo Cao, Tao Cheng   +9 more
wiley   +1 more source

HSTXGB: a hyperparameter self-tuning XGBoost method integrating pre- and post-processing for gene regulatory network inference. [PDF]

Front Genet
Huang M, Guo S, Jiang F, Xiong Y, Chen X.   +4 more
europepmc   +1 more source

A systematic review of hyperparameter optimization techniques in Convolutional Neural Networks

Decision Analytics Journal
Mohaimenul Azam Khan Raiaan, Sadman Sakib, Nur Mohammad Fahad, A. al Mamun, Md. Anisur Rahman, Swakkhar Shatabda, M. Mukta   +6 more
semanticscholar   +1 more source

A Closed‐Loop Framework for Inverse Design: Dynamic Training and Intelligent Optimization for Heterostructured Materials

Advanced Science, EarlyView.
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong, Xueru Zheng, Xiao Zhou, Zhengheng Tao, Wan Han, Jingyi Pan, Dian Wu, Ning Gao, Lei Liu, Zhongyang Wang, Fanchao Meng, Tongxiang Fan   +11 more
wiley   +1 more source

An Optimized and Explainable Machine Learning Framework for Diabetes Prediction Using Marine Predators Algorithm and SHAP. [PDF]

J Pers Med
Nasrin A, Asif MB, Naidu R, Asif AH, Chohan MS, Khan GA, Arifuzzaman M, Azad A, Martuza MA.   +8 more
europepmc   +1 more source

Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations

Advanced Science, EarlyView.
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford, Matthew Tamasi, Elena Di Mare, Adam J. Gormley   +3 more
wiley   +1 more source

DDSurfer: A Weakly‐Supervised Dual‐Stream Deep Learning Framework for Cortical Surface Reconstruction From Diffusion MRI

Advanced Science, EarlyView.
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li, Wei Zhang, Xi Zhu, Yuqian Chen, Nir A. Sochen, Jarrett Rushmore, Carl‐Fredrik Westin, Yogesh Rathi, Lauren J. O'Donnell, Ofer Pasternak, Fan Zhang   +10 more
wiley   +1 more source

Sustainable Hyperparameter Optimization

https://www.ieeesmc.org/cai-2026/tutorial-7-sustainable-hyperparameter-optimization/ https://github.com/ai-for-decision-making-tue ...
Bliek, Laurens, AMINI, Sasan
core   +1 more source

Bio-Inspired Enhanced Adaptive Centered Collision Optimizer for Hyperparameter Optimization of Multi-Scale Spatio-Temporal ConvNeXt in Boxing Action Recognition. [PDF]

Biomimetics (Basel)
Liu T.
europepmc   +1 more source