6 citations · 10 across the 5 of their papers we have counts for
5 papers
Latent Anomaly Detection Through Density Matrices
Joseph Gallego-Mejia, Oscar Bustos-Brinez, Fabio A. González
This paper introduces a novel anomaly detection framework that combines the robust statistical principles of density-estimation-based anomaly detection methods with the representat…
LEAN-DMKDE: Quantum Latent Density Estimation for Anomaly Detection
Joseph Gallego-Mejia, Oscar Bustos-Brinez, Fabio A. González
This paper presents an anomaly detection model that combines the strong statistical foundation of density-estimation-based anomaly detection methods with the representation-learnin…
AD-DMKDE: Anomaly Detection through Density Matrices and Fourier Features
Oscar Bustos-Brinez, Joseph Gallego-Mejia, Fabio A. González
This paper presents a novel density estimation method for anomaly detection using density matrices (a powerful mathematical formalism from quantum mechanics) and Fourier features.…
InQMAD: Incremental Quantum Measurement Anomaly Detection
Joseph Gallego-Mejia, Oscar Bustos-Brinez, Fabio Gonzalez
Streaming anomaly detection refers to the problem of detecting anomalous data samples in streams of data. This problem poses challenges that classical and deep anomaly detection me…
Quantum density estimation with density matrices: Application to quantum anomaly detection
Diego H. Useche, Oscar A. Bustos-Brinez, Joseph A. Gallego-Mejia +1
Density estimation is a central task in statistics and machine learning. This problem aims to determine the underlying probability density function that best aligns with an observe…