1 citations · 1 across the 1 of their papers we have counts for
3 papers
physics.comp-ph2019★ 1 cited
Solving Partial Differential Equations with Neural Networks
Juan B. Pedro, Juan Maroñas, Roberto Paredes
Many scientific and industrial applications require solving Partial Differential Equations (PDEs) to describe the physical phenomena of interest. Some examples can be found in the…
cs.LG2019
Calibration of Deep Probabilistic Models with Decoupled Bayesian Neural Networks
Juan Maroñas, Roberto Paredes, Daniel Ramos
Deep Neural Networks (DNNs) have achieved state-of-the-art accuracy performance in many tasks. However, recent works have pointed out that the outputs provided by these models are…
cs.LG2019
Generative Models For Deep Learning with Very Scarce Data
Juan Maroñas, Roberto Paredes, Daniel Ramos
The goal of this paper is to deal with a data scarcity scenario where deep learning techniques use to fail. We compare the use of two well established techniques, Restricted Boltzm…