27 citations · 44 across the 10 of their papers we have counts for
7 papers · 1 filter
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…
Risk Automatic Prediction for Social Economy Companies using Camels
Joseph Gallego-Mejia, Daniela Martin-Vega, Fabio Gonzalez
Governments have to supervise and inspect social economy enterprises (SEEs). However, inspecting all SEEs is not possible due to the large number of SEEs and the low number of insp…
Fast Kernel Density Estimation with Density Matrices and Random Fourier Features
Joseph A. Gallego, Juan F. Osorio, Fabio A. González
Kernel density estimation (KDE) is one of the most widely used nonparametric density estimation methods. The fact that it is a memory-based method, i.e., it uses the entire trainin…
Quantum Adaptive Fourier Features for Neural Density Estimation
Joseph A. Gallego, Fabio A. González
Density estimation is a fundamental task in statistics and machine learning applications. Kernel density estimation is a powerful tool for non-parametric density estimation in low…
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…