Abstract: Predicting information popularity in social networks has become a central focus of network analysis. While recent advancements have been made, most existing approaches rely solely on the ...

The interaction between the molecular chaperone 14-3-3σ and the intrinsically disordered protein α-synuclein is implicated in the pathogenesis of Parkinson’s disease, yet its dynamic mechanism remains ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...

This repository contains the code and models used in the paper "Understanding European Heatwaves with Variational Autoencoders" submitted to Earth System Dynamics ...

Abstract: Variational autoencoders are employed to provide a framework for learning deep latent state representation. Inverse autoregressive flow is a type of normalizing flow that is employed to ...

Generative Modeling is a branch of machine learning that focuses on creating models representing distributions of data, denoted as $P(X)$. $X$ represents the data ...

Deep learning methods for generating artificial data in health care include data augmentation by variational autoencoders (VAE) technology. Objective: We aimed to test the feasibility of generating ...

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...

Antonia Haynes is a Game Rant writer who resides in a small seaside town in England where she has lived her whole life. Beginning her video game writing career in 2014, and having an avid love of ...

Robbie has been an avid gamer for well over 20 years. During that time, he's watched countless franchises rise and fall. He's a big RPG fan but dabbles in a little bit of everything. Writing about ...