If you've spent any time with ChatGPT or another AI chatbot, you've probably noticed they are intensely, almost overbearingly ...
The coral reef ecosystems of the Maldives are critical to the nation’s ecological integrity, economic development, and ...
A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
Breast cancer is a highly heterogeneous malignancy among women worldwide. Traditional prognostic models relying solely on ...
Abstract: Reliability analysis for structural systems relies on an accurate surrogate model. Currently, several multiple Kriging methods are utilized to calculate the failure probability. However, ...
This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...
Empowered by technological progress, sports teams and bookmakers strive to understand relationships between player and team activity and match outcomes. For this purpose, the probability of an event ...
We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
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