39 citations · 47 across the 8 of their papers we have counts for
8 papers
Quantum generative classification with mixed states
Diego H. Useche, Sergio Quiroga-Sandoval, Sebastian L. Molina +3
Classification can be performed using either a discriminative or a generative learning approach. Discriminative learning consists of constructing the conditional probability of the…
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…
MEMO-QCD: Quantum Density Estimation through Memetic Optimisation for Quantum Circuit Design
Juan E. Ardila-García, Vladimir Vargas-Calderón, Fabio A. González +2
This paper presents a strategy for efficient quantum circuit design for density estimation. The strategy is based on a quantum-inspired algorithm for density estimation and a circu…
Interpreting Themes from Educational Stories
Yigeng Zhang, Fabio A. González, Thamar Solorio
Reading comprehension continues to be a crucial research focus in the NLP community. Recent advances in Machine Reading Comprehension (MRC) have mostly centered on literal comprehe…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
On-orbit model training for satellite imagery with label proportions
Raúl Ramos-Pollán, Fabio A. González
This work addresses the challenge of training supervised machine or deep learning models on orbiting platforms where we are generally constrained by limited on-board hardware capab…
Kernel Density Matrices for Probabilistic Deep Learning
Fabio A. González, Raúl Ramos-Pollán, Joseph A. Gallego-Mejia
This paper introduces a novel approach to probabilistic deep learning, kernel density matrices, which provide a simpler yet effective mechanism for representing joint probability d…
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…