activity
20172022
most citedExtreme Learning Machine design for dealing with unrepresentative features

1 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.HC20221 cited

A Collaborative, Interactive and Context-Aware Drawing Agent for Co-Creative Design

Francisco Ibarrola, Tomas Lawton, Kazjon Grace

Recent advances in text-conditioned generative models have provided us with neural networks capable of creating images of astonishing quality, be they realistic, abstract, or even…

cs.LG20201 cited

Partially Conditioned Generative Adversarial Networks

Francisco J. Ibarrola, Nishant Ravikumar, Alejandro F. Frangi

Generative models are undoubtedly a hot topic in Artificial Intelligence, among which the most common type is Generative Adversarial Networks (GANs). These architectures let one sy…

cs.LG20191 cited

Extreme Learning Machine design for dealing with unrepresentative features

Nicolás Nieto, Francisco Ibarrola, Victoria Peterson +2

Extreme Learning Machines (ELMs) have become a popular tool in the field of Artificial Intelligence due to their very high training speed and generalization capabilities. Another a…

cs.SD2018

Switching divergences for spectral learning in blind speech dereverberation

Francisco Ibarrola, Leandro Di Persia, Ruben Spies

When recorded in an enclosed room, a sound signal will most certainly get affected by reverberation. This not only undermines audio quality, but also poses a problem for many human…

cs.SD2017

Mixed penalization in convolutive nonnegative matrix factorization for blind speech dereverberation

Francisco J. Ibarrola, Leandro E. Di Persia, Ruben D. Spies

When a signal is recorded in an enclosed room, it typically gets affected by reverberation. This degradation represents a problem when dealing with audio signals, particularly in t…