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QKSA: Quantum Knowledge Seeking Agent
In this research, we extend the universal reinforcement learning agent models of artificial general intelligence to quantum environments. The utility...
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Vibration-Based Structural Damage Detection Using Sparse Bayesian Learning Techniques
Vibration-based structural damage detection constantly involves uncertainties, including measurement noise, methodology, and modeling errors....
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Whiteness Constraints in a Unified Variational Framework for Image Restoration
We propose a robust variational model for the restoration of images corrupted by blur and the general class of additive white noises. The key idea...
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Rényi Relative Entropy from Homogeneous Kullback-Leibler Divergence Lagrangian
We study the homogeneous extension of the Kullback-Leibler divergence associated to a covariant variational problem on the statistical bundle. We...
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Visual Analytics Tools for the Study of Complex Problems in Engineering and Biomedicine
In this article, we present the main lines of an ongoing research project funded by the Spanish government. The project proposes research on visual...
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On the Characterization of Saddle Point Equilibrium for Security Games with Additive Utility
In this work, we investigate a security game between an attacker and a defender, originally proposed in [6]. As is well known, the combinatorial...
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Disentangling Geometric Deformation Spaces in Generative Latent Shape Models
A complete representation of 3D objects requires characterizing the space of deformations in an interpretable manner, from articulations of a single...
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Deep Cardiac MRI Reconstruction with ADMM
Cardiac magnetic resonance imaging (CMR) is a valuable non-invasive tool for identifying cardiovascular diseases. For instance, Cine MRI is the...
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Can Point Cloud Networks Learn Statistical Shape Models of Anatomies?
Statistical Shape Modeling (SSM) is a valuable tool for investigating and quantifying anatomical variations within populations of anatomies. However,...
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Theory of overparametrization in quantum neural networks
The prospect of achieving quantum advantage with quantum neural networks (QNNs) is exciting. Understanding how QNN properties (for example, the...
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Adversarial Defense Mechanisms for Supervised Learning
In this chapter we explore neural network architectures, implementations, cost analysis, and training processes using game theoretical adversarial...
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Deep Learning-based Coronary Stenosis Detection in X-ray Angiography Images: Overview and Future Trends
Deep learning methods, particularly Convolutional Neural Networks, have been successfully applied in medical imaging. Robust stenosis detection in...
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Background on Machine Learning Techniques
Machine learning techniques have been widely used over the years to enhance several security functions. This chapter provides an introduction to the...
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Target and Precursor Named Entities Recognition from Scientific Texts of High-Temperature Steel Using Deep Neural Network
Named Entity Recognition (NER) is an essential task in natural language processing, especially in the domain of scientific texts. This paper presents...
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Effective COVID-19 disease identification using correlation coefficient absolute feature selection and logistic boosting neural network algorithm
The recently identified coronavirus, or COVID-19, is a pandemic that has had a significant impact on global financial and social problems. To mediate...
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A Variational Basis for the Regulation and Structuration Mechanisms of Core Operatory Structures
In this chapter, we introduce a set of operations (called variations) that support the regulation and the structuration mechanisms of core operatory...
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Self-adaptive gradient projection algorithms for variational inequalities involving non-Lipschitz continuous operators
In this paper, we introduce a self-adaptive inertial gradient projection algorithm for solving monotone or strongly pseudomonotone variational...
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Crystallography companion agent for high-throughput materials discovery
The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has...
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A literature review and perspectives in deepfakes: generation, detection, and applications
In the last few years, with the advancement of deep learning methods, especially Generative Adversarial Networks (GANs) and Variational Auto-encoders...
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On Bayesian Posterior Mean Estimators in Imaging Sciences and Hamilton–Jacobi Partial Differential Equations
Variational and Bayesian methods are two widely used set of approaches to solve image denoising problems. In a Bayesian setting, these approaches...
