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07/20/2023
From computational ethics to morality: how decision-making algorithms can help us understand the emergence of moral principles, the existence of an optimal behaviour and our ab
This paper adds to the efforts of evolutionary ethics to naturalize mora...
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06/05/2023
A survey of Generative AI Applications
Generative AI has experienced remarkable growth in recent years, leading...
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05/05/2023
Simulating H.P. Lovecraft horror literature with the ChatGPT large language model
In this paper, we present a novel approach to simulating H.P. Lovecraft'...
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04/06/2023
ChatGPT: More than a Weapon of Mass Deception, Ethical challenges and responses from the Human-Centered Artificial Intelligence (HCAI) perspective
This article explores the ethical problems arising from the use of ChatG...
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03/21/2023
Fine-tuning ClimateBert transformer with ClimaText for the disclosure analysis of climate-related financial risks
In recent years there has been a growing demand from financial agents, e...
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01/11/2023
ChatGPT is not all you need. A State of the Art Review of large Generative AI models
During the last two years there has been a plethora of large generative ...
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12/08/2022
Optimizing Integrated Information with a Prior Guided Random Search Algorithm
Integrated information theory (IIT) is a theoretical framework that prov...
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08/03/2022
On the independence between phenomenal consciousness and computational intelligence
Consciousness and intelligence are properties commonly understood as dep...
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07/22/2022
Do Artificial Intelligence Systems Understand?
Are intelligent machines really intelligent? Is the underlying philosoph...
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06/15/2022
Multi-Objective Hyperparameter Optimization – An Overview
Hyperparameter optimization constitutes a large part of typical modern m...
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07/08/2021
Many Objective Bayesian Optimization
Some real problems require the evaluation of expensive and noisy objecti...
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01/20/2021
A Similarity Measure of Gaussian Process Predictive Distributions
Some scenarios require the computation of a predictive distribution of a...
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11/30/2020
An Artificial Consciousness Model and its relations with Philosophy of Mind
This work seeks to study the beneficial properties that an autonomous ag...
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11/24/2020
Fuzzy Stochastic Timed Petri Nets for Causal properties representation
Imagery is frequently used to model, represent and communicate knowledge...
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05/26/2020
Comparing BERT against traditional machine learning text classification
The BERT model has arisen as a popular state-of-the-art machine learning...
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04/01/2020
Parallel Predictive Entropy Search for Multi-objective Bayesian Optimization with Constraints
Real-world problems often involve the optimization of several objectives...
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03/21/2020
Towards Automatic Bayesian Optimization: A first step involving acquisition functions
Bayesian Optimization is the state of the art technique for the optimiza...
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02/04/2020
Fake News Detection by means of Uncertainty Weighted Causal Graphs
Society is experimenting changes in information consumption, as new info...
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02/02/2020
A Machine Consciousness architecture based on Deep Learning and Gaussian Processes
Recent developments in machine learning have pushed the tasks that machi...
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02/02/2020
Uncertainty Weighted Causal Graphs
Causality has traditionally been a scientific way to generate knowledge ...
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01/28/2020
Multi-class Gaussian Process Classification with Noisy Inputs
It is a common practice in the supervised machine learning community to ...
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11/09/2018
Suggesting Cooking Recipes Through Simulation and Bayesian Optimization
Cooking typically involves a plethora of decisions about ingredients and...
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06/28/2018
Bayesian optimization of the PC algorithm for learning Gaussian Bayesian networks
The PC algorithm is a popular method for learning the structure of Gauss...
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05/09/2018
Dealing with Categorical and Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Bayesian Optimization (BO) methods are useful for optimizing functions t...
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06/12/2017
Dealing with Integer-valued Variables in Bayesian Optimization with Gaussian Processes
Bayesian optimization (BO) methods are useful for optimizing functions t...
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09/05/2016
