S. Hernández

Smoothing Algorithms for the Probability Hypothesis Density Filter

Sergio Hernández, S. Hernández, 2010 .

On line Bayesian tracking and detection of multiple objects

S. Hernández, 2008 .

Improving predictive uncertainty estimation using Dropout–Hamiltonian Monte Carlo

Matias Valdenegro-Toro, S. Hernández, Diego Vergara, 2019, Soft Computing.

Multi-target Tracking with Poisson Processes Observations

Paul D. Teal, Sergio Hernández, S. Hernández, 2007, PSIVT.

State Estimation and  Smoothing for the  Probability Hypothesis  Density Filter

S. Hernández, 2010 .

Improving predictive uncertainty estimation using Dropout–Hamiltonian Monte Carlo

Matias Valdenegro-Toro, Felipe Jorquera, Diego Vergara, 2018, Soft Comput..

Evaluating deep learning predictions for COVID-19 from X-ray images using leave-one-out predictive densities

Xaviera A. López-Cortés, S. Hernández, 2023, Neural Computing and Applications.

Multinomial Naive Bayes for real-time gender recognition

Diego Vergara, Felipe Jorquera, Sergio Hernandez, 2016, 2016 XXI Symposium on Signal Processing, Images and Artificial Vision (STSIVA).

Predictive Uncertainty in Large Scale Classification using Dropout - Stochastic Gradient Hamiltonian Monte Carlo pdf

Matias Valdenegro-Toro, Sergio Hernández, Diego Vergara, 2018, ArXiv.

A Comparison of Stochastic Gradient MCMC using Multi-Core and GPU Architectures

Sergio Hernández, José Valdés, Matias Valdenegro, 2020, 2020 Congreso Estudiantil de Electrónica y Electricidad (INGELECTRA).