Abstract: As awareness of data privacy protection continues to grow, many-task optimization faces a significant challenge in balancing privacy protection and performance improvement. This paper ...

This webinar introduced healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this paper, we introduce a methodology to improve upon the ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Zelensky makes major concession to ...

EarthArxiv preprint now available https://doi.org/10.31223/X57T5R! ADCIRC forcing and processing. Some generic mesh processing. Assumes gradient wind reduction factor ...

1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China 2 State Key Laboratory of Mountain Bridge and Tunnel Engineering, ...

Abstract: The standard Bayesian optimization algorithm encounters the curse of dimensionality in high-dimensional problems. The difficulty of optimizing the acquisition function increases, resulting ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...