A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

Prophet has added Phil Davis to its advisory board.The announcement:Prophet, the decision intelligence company building ...

Here’s what you’ll learn when you read this story: In May of 2019, a short-duration binary black hole (BBH) merger contained no evidence of the inspiral signal typical of these kinds of a ...

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 ...

Lipid Domain Transport Analyzer A comprehensive analysis toolkit for studying target lipid-mediated protein transport to cholesterol-rich membrane domains using Hidden Markov Models and Bayesian ...

Purpose: Bayesian approaches may improve the efficiency of trials and accelerate decision-making, but reluctance to depart from traditional frequentist statistics may limit their use. Because oncology ...

Bayesian methods for inference and prediction have become widespread in the social sciences (and beyond). Over the last decades, applied Bayesian modeling has evolved from a niche methodology with ...

Abstract: Estimating the probability of rare channel conditions is a central challenge in ultra-reliable wireless communication, where random events, such as deep fades, can cause sudden variations in ...

This study explores the application of Bayesian econometrics in policy evaluation through theoretical analysis. The research first reviews the theoretical foundations of Bayesian methods, including ...