295 citations · 1.1k across the 17 of their papers we have counts for
9 papers · 1 filter
An Artificial Consciousness Model and its relations with Philosophy of Mind
Eduardo C. Garrido-Merchán, Martin Molina, Francisco M. Mendoza
This work seeks to study the beneficial properties that an autonomous agent can obtain by implementing a cognitive architecture similar to the one of conscious beings. Along this d…
Fuzzy Stochastic Timed Petri Nets for Causal properties representation
Alejandro Sobrino, Eduardo C. Garrido-Merchan, Cristina Puente
Imagery is frequently used to model, represent and communicate knowledge. In particular, graphs are one of the most powerful tools, being able to represent relations between object…
Comparing BERT against traditional machine learning text classification
Santiago González-Carvajal, Eduardo C. Garrido-Merchán
The BERT model has arisen as a popular state-of-the-art machine learning model in the recent years that is able to cope with multiple NLP tasks such as supervised text classificati…
Fake News Detection by means of Uncertainty Weighted Causal Graphs
Eduardo C. Garrido-Merchán, Cristina Puente, Rafael Palacios
Society is experimenting changes in information consumption, as new information channels such as social networks let people share news that do not necessarily be trust worthy. Some…
Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints
Eduardo C. Garrido-Merchán, Daniel Hernández-Lobato
Real-world problems often involve the optimization of several objectives under multiple constraints. An example is the hyper-parameter tuning problem of machine learning algorithms…
A Machine Consciousness architecture based on Deep Learning and Gaussian Processes
Eduardo C. Garrido Merchán, Martín Molina
Recent developments in machine learning have pushed the tasks that machines can do outside the boundaries of what was thought to be possible years ago. Methodologies such as deep l…
Towards Automatic Bayesian Optimization: A first step involving acquisition functions
Eduardo C. Garrido Merchán, Luis C. Jariego Pérez
Bayesian Optimization is the state of the art technique for the optimization of black boxes, i.e., functions where we do not have access to their analytical expression nor its grad…
Uncertainty Weighted Causal Graphs
Eduardo C. Garrido-Merchán, C. Puente, A. Sobrino +1
Causality has traditionally been a scientific way to generate knowledge by relating causes to effects. From an imaginery point of view, causal graphs are a helpful tool for represe…
Multi-class Gaussian Process Classification with Noisy Inputs
Carlos Villacampa-Calvo, Bryan Zaldivar, Eduardo C. Garrido-Merchán +1
It is a common practice in the machine learning community to assume that the observed data are noise-free in the input attributes. Nevertheless, scenarios with input noise are comm…