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 ...

ABSTRACT: Anomaly detection in complex crowd scenes is a challenging task due to the inherent variability in crowd behaviors, interactions, and scales. This paper proposes a novel hybrid model that ...

Completing the GTA Online tutorial involves a few steps, including creating your character, meeting Lamar, and completing a few missions. While we would not suggest skipping the tutorial, there are a ...

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 ...

Abstract: Vector quantized variational autoencoders, as variants of variational autoencoders, effectively capture discrete representations by quantizing continuous latent spaces and are widely used in ...

The sequence of amino acids within a protein dictates its structure and function. Protein engineering campaigns seek to discover protein sequences with desired functions. Data-driven models of the ...