Results 111 to 120 of about 289,279 (277)

Interpretable machine learning approach for TBM tunnel crown convergence prediction with Bayesian optimization

Frontiers in Earth Science
Accurate prediction of crown convergence in Tunnel Boring Machine (TBM) tunnels is critical for ensuring construction safety, optimizing support design, and improving construction efficiency.
Wanrui Hu, Kai Wu, Kai Wu, Heng Liu, Weibang Luo, Xingxing Li, Peng Guan   +6 more
doaj   +1 more source

Spintronic Bayesian Hardware Driven by Stochastic Magnetic Domain Wall Dynamics

Advanced Science, EarlyView.
Magnetic Probabilistic Computing (MPC) utilizes intrinsic stochastic dynamics in domain walls to establish a hardware foundation for uncertainty‐aware artificial intelligence. Thermally driven domain‐wall fluctuations, voltage‐controlled magnetic anisotropy, and TMR readout enable fully electrical, tunable probabilistic inference.
Tianyi Wang, Bingqian Dai, Shijie Xu, Kin Wong, Yaochen Li, Yang Cheng, Qingyuan Shu, Haoran He, Puyang Huang, Hanshen Huang, Xixiang Zhang, Kang L. Wang   +11 more
wiley   +1 more source

Sensor-Oriented Framework for Underwater Acoustic Signal Classification Using EMD–Wavelet Filtering and Bayesian-Optimized Random Forest

Sensors
Ship acoustic signal classification is essential for vessel identification, underwater navigation, and maritime security. Traditional methods struggle with the non-stationary nature and noise of ship acoustic signals, reducing classification accuracy. To
Sergii Babichev, Oleg Yarema, Yevheniy Khomenko, Denys Senchyshen, Bohdan Durnyak   +4 more
doaj   +1 more source

Preferential Bayesian Optimization

, 2017
Bayesian optimization (BO) has emerged during the last few years as an effective approach to optimizing black-box functions where direct queries of the objective are expensive. In this paper we consider the case where direct access to the function is not possible, but information about user preferences is.
Gonzalez, Javier, Dai, Zhenwen, Damianou, Andreas, Lawrence, Neil D.   +3 more
openaire   +2 more sources

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

Temperature prediction model for coal spontaneous combustion based on Bayesian optimization support vector regression

Gong-kuang zidonghua
To address the issue that traditional coal spontaneous combustion temperature prediction models do not consider multicollinearity between indicator gases and temperature data and have insufficient prediction accuracy, a coal spontaneous combustion ...
YANG Haiyan, HU Xincheng, CAI Jiawen, YU Zhaoyang   +3 more
doaj   +1 more source

A Scalable Framework for Comprehensive Typing of Polymorphic Immune Genes from Long‐Read Data

Advanced Science, EarlyView.
SpecImmune introduces a unified computational framework optimized for long‐read sequencing to resolve over 400 highly polymorphic immune genes. This scalable approach achieves high‐resolution typing, enabling the discovery of cross‐family co‐evolutionary networks and population‐specific diversity.
Shuai Wang, Xuedong Wang, Mengyao Wang, Qian Zhou, Lusheng Wang, Shuai Cheng Li   +5 more
wiley   +1 more source

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

GeoAI-Enabled Ensemble Modeling to Assess Land Use and Atmospheric Pollutant Impacts on Land Surface Temperature in the US Southwest

Remote Sensing
The US Southwest is one of the driest and hottest regions, with a recent upsurge in land surface temperature (LST). Further, with land-use changes and global warming, anthropogenic pollution also significantly contributes to the rise in surface ...
Bijoy Mitra, Guiming Zhang
doaj   +1 more source

Optimizing Bayesian optimization

, 2019
We are concerned primarily with improving the practical applicability of Bayesian optimization. We make contributions in three key areas. We develop an intuitive online stopping criterion, allowing only as many steps as necessary to achieve the desired target to be taken.
openaire   +1 more source