Argitalpenak (22) MANUEL LOPEZ MARTIN argitalpenak

2024

  1. Deep learning combined with singular value decomposition to reconstruct databases in fluid dynamics[Formula presented]

    Expert Systems with Applications, Vol. 238

  2. ModelFLOWs-app: Data-driven post-processing and reduced order modelling tools

    Computer Physics Communications, Vol. 301

2023

  1. Contrastive Learning over Random Fourier Features for IoT Network Intrusion Detection

    IEEE Internet of Things Journal, Vol. 10, Núm. 10, pp. 8505-8513

  2. Forecasting through deep learning and modal decomposition in two-phase concentric jets

    Expert Systems with Applications, Vol. 232

2022

  1. A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures[Formula presented]

    Expert Systems with Applications, Vol. 187

  2. Supervised contrastive learning over prototype-label embeddings for network intrusion detection

    Information Fusion, Vol. 79, pp. 200-228

2021

  1. Additive ensemble neural network with constrained weighted quantile loss for probabilistic electric‐load forecasting

    Sensors, Vol. 21, Núm. 9

  2. Model-free short-term fluid dynamics estimator with a deep 3D-convolutional neural network

    Expert Systems with Applications, Vol. 177

  3. Network Intrusion Detection Based on Extended RBF Neural Network with Offline Reinforcement Learning

    IEEE Access, Vol. 9, pp. 153153-153170

  4. Network intrusion detection with a novel hierarchy of distances between embeddings of hash IP addresses

    Knowledge-Based Systems, Vol. 219

  5. Novel data-driven models applied to short-term electric load forecasting

    Applied Sciences (Switzerland), Vol. 11, Núm. 12

2020

  1. Application of deep reinforcement learning to intrusion detection for supervised problems

    Expert Systems with Applications, Vol. 141

  2. Detection of early stages of Alzheimer's disease based on MEG activity with a randomized convolutional neural network

    Artificial Intelligence in Medicine, Vol. 107

  3. IoT type-of-traffic forecasting method based on gradient boosting neural networks

    Future Generation Computer Systems, Vol. 105, pp. 331-345

2019

  1. Adversarial environment reinforcement learning algorithm for intrusion detection

    Computer Networks, Vol. 159, pp. 96-109

  2. Neural network architecture based on gradient boosting for IoT traffic prediction

    Future Generation Computer Systems, Vol. 100, pp. 656-673

  3. Shallow neural network with kernel approximation for prediction problems in highly demanding data networks

    Expert Systems with Applications, Vol. 124, pp. 196-208

  4. Variational data generative model for intrusion detection

    Knowledge and Information Systems, Vol. 60, Núm. 1, pp. 569-590

2018

  1. Deep Learning Model for Multimedia Quality of Experience Prediction Based on Network Flow Packets

    IEEE Communications Magazine, Vol. 56, Núm. 9, pp. 110-117

2017

  1. Conditional variational autoencoder for prediction and feature recovery applied to intrusion detection in iot

    Sensors (Switzerland), Vol. 17, Núm. 9