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Gonzalo Joya
- ESANN 2005 - Stochastic analysis of the Abe formulation of Hopfield networks [Details]
- ESANN 2005 - Two or three things that we (intend to) know about Hopfield and Tank networks [Details]
- ESANN 2011 - Statistical properties of the `Hopfield estimator' of dynamical systems [Details]
- ESANN 2009 - Gaussian Mixture Models for multiclass problems with performance constraints [Details]
- ESANN 2011 - Identification of sparse spatio-temporal features in Evoked Response Potentials [Details]
- No papers found
- ESANN 2022 - 1D vs 2D convolutional neural networks for scalp high frequency oscillations identification [Details]
- ESANN 2010 - Segmentation of EMG time series using a variational Bayesian approach for the robust estimation of cortical silent periods [Details]
- ESANN 2008 - DSS-oriented exploration of a multi-centre magnetic resonance spectroscopy brain tumour dataset through visualization [Details]
- ESANN 2010 - Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis [Details]
- ESANN 2016 - A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases [Details]
- ESANN 2016 - Fast in-memory spectral clustering using a fixed-size approach [Details]
- ESANN 2023 - A model-based approach to meta-Reinforcement Learning: Transformers and tree search [Details]
- ESANN 2015 - A new genetic algorithm for multi-label correlation-based feature selection [Details]
- ESANN 2020 - Binary and Multi-label Defect Classification of Printed Circuit Board based on Transfer Learning [Details]
- ESANN 2020 - CNN Encoder to Reduce the Dimensionality of Data Image for Motion Planning [Details]
- ESANN 2023 - Evaluation of Contrastive Learning for Electronic Component Detection [Details]
- ESANN 2018 - Structuring and Solving Multi-Criteria Decision Making Problems using Artificial Neural Networks: a smartphone recommendation case [Details]
- ESANN 1994 - A comparison of two weight pruning methods [Details]
- ESANN 1995 - Invited paper: Pruning methods: a review [Details]
- ESANN 1995 - Pruning kernel density estimators [Details]
- ESANN 1996 - Combining sigmoids and radial basis functions in evolutive neural architectures [Details]
- ESANN 1997 - From source separation to Independent Component Analysis: an introduction to the special session [Details]
- ESANN 1997 - Nonlinear source separation: the post-nonlinear mixtures [Details]
- ESANN 1998 - Improving neural network estimation in presence of non i.i.d. noise [Details]
- ESANN 2000 - Parametric approach to blind deconvolution of nonlinear channels [Details]
- ESANN 2003 - Acceptability conditions for BSS problems [Details]
- ESANN 2006 - Semi-Blind Approaches for Source Separation and Independent component Analysis [Details]
- ESANN 2008 - A Methodology for Building Regression Models using Extreme Learning Machine: OP-ELM [Details]
- ESANN 2009 - Sparse differential connectivity graph of scalp EEG for epileptic patients [Details]
- ESANN 2009 - Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics [Details]
- ESANN 2010 - Ensemble Modeling with a Constrained Linear System of Leave-One-Out Outputs [Details]
- ESANN 2012 - Application of Dynamic Time Warping on Kalman Filtering Framework for Abnormal ECG Filtering [Details]
- ESANN 2012 - BCI Signal Classification using a Riemannian-based kernel [Details]
- ESANN 2012 - The error-related potential and BCIs [Details]
- ESANN 2016 - Unsupervised Cross-Subject BCI Learning and Classification using Riemannian Geometry [Details]