Electronic proceedings author index

A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z
Renato Socodato
  • ESANN 2016 - Stacked denoising autoencoders for the automatic recognition of microglial cells’ state [Details]
G. Soda
  • ESANN 1999 - A topological transformation for hidden recursive modelsarchitecture networks [Details]
Boussa Sofiane
  • ESANN 2005 - Experimental validation of a synapse model by adding synaptic conductances to excitable endocrine cells in culture [Details]
Anders Søgaard
  • ESANN 2017 - Spikes as regularizers [Details]
Andrei Soklakov
  • ESANN 2005 - A probabilistic framework for mismatch and profile string kernels [Details]
Fabio Solari
  • ESANN 2009 - A neural model for binocular vergence control without explicit calculation of disparity [Details]
Amparo Soldevila
  • ESANN 2010 - Neural models for the analysis of kidney disease patients [Details]
J. Sole i Casals
  • ESANN 2000 - Parametric approach to blind deconvolution of nonlinear channels [Details]
Behrouz Haji Soleimani
  • ESANN 2017 - Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification [Details]
Andres Soler
  • ESANN 2024 - EEG Source Imaging Enhances Motor Imagery Classification [Details]
S. A. Solla
  • ESANN 1997 - Bayesian online learning in the perceptron [Details]
Rudolf Sollacher
  • ESANN 2007 - Spiral Recurrent Neural Network for Online Learning [Details]
  • ESANN 2008 - Conditional prediction of time series using spiral recurrent neural network [Details]
P. Sollich
  • ESANN 1995 - Minimum entropy queries for linear students learning nonlinear rules [Details]
D.P. Solomatine
  • ESANN 2003 - Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river [Details]
S. Soltani
  • ESANN 2000 - On the use of the wavelet decomposition for time series prediction [Details]
Hamid Soltanian-Zadeh
  • ESANN 2009 - Sparse differential connectivity graph of scalp EEG for epileptic patients [Details]
G. Sommer
  • ESANN 1996 - Praticing Q-learning [Details]
  • ESANN 2000 - Quaternionic spinor MLP [Details]
  • ESANN 2003 - The hypersphere neuron [Details]
Gerald Sommer
  • ESANN 2005 - Efficient reinforcement learning through Evolutionary Acquisition of Neural Topologies [Details]
Qing Song
  • ESANN 2005 - Adaptive Simultaneous Perturbation Based Pruning Algorithm for Neural Control Systems [Details]
Yang Song
  • ESANN 2014 - Neural network based 2D/3D fusion for robotic object recognition [Details]
Laurent Sorber
  • ESANN 2020 - An agile machine learning project in pharma - developing a Mask R-CNN-based web application for bacterial colony counting [Details]
August Sørensen
  • ESANN 2019 - Detecting Ghostwriters in High Schools [Details]
Antonio Sorgente
  • ESANN 2023 - Improving the DRASiW performance by exploiting its own "Mental Images" [Details]
  • ESANN 2024 - ''Mental Images'' driven classification [Details]
  • ESANN 2025 - Hierarchical decomposition through "Mental Images" evaluation [Details]
Antonio Sorgente
  • ESANN 2021 - Weightless Neural Networks for text classification using tf-idf [Details]
  • ESANN 2022 - Classification of preclinical markers in Alzheimer's disease via WiSARD classifier [Details]
Emilio Soria
  • ESANN 2010 - Neural models for the analysis of kidney disease patients [Details]
  • ESANN 2011 - Analysis of a Reinforcement Learning algorithm using Self-Organizing Maps [Details]
  • ESANN 2011 - Growing Hierarchical Sectors on Sectors [Details]
Emilio Soria Olivas
  • ESANN 2021 - End-to-end Keyword Spotting using Xception-1d [Details]
Emilio Soria-Olivas
  • ESANN 2012 - Regularized Committee of Extreme Learning Machine for Regression Problems [Details]
  • ESANN 2012 - extended visualization method for classification trees [Details]
  • ESANN 2013 - Least-squares temporal difference learning based on extreme learning machine [Details]
  • ESANN 2013 - Machine Learning Techniques for Short-Term Electric Power Demand Prediction [Details]
  • ESANN 2013 - ManiSonS: A New Visualization Tool for Manifold Clustering [Details]
  • ESANN 2013 - Temperature Forecast in Buildings Using Machine Learning Techniques [Details]
  • ESANN 2014 - Ensembles of extreme learning machine networks for value prediction [Details]
  • ESANN 2016 - Multi-step strategy for mortality assessment in cardiovascular risk patients with imbalanced data [Details]
  • ESANN 2017 - Randomized Machine Learning Approaches: Recent Developments and Challenges [Details]
Antti Sorjamaa
  • ESANN 2005 - Pruned lazy learning models for time series prediction [Details]
  • ESANN 2006 - Time series prediction using DirRec strategy [Details]
  • ESANN 2007 - SOM+EOF for finding missing values [Details]
  • ESANN 2009 - X-SOM and L-SOM: a nested approach for missing value imputation [Details]
Andrea Sorrentino
  • ESANN 2019 - Explaining classification systems using sparse dictionaries [Details]
Axel J. Soto
  • ESANN 2010 - Adaptive matrix distances aiming at optimum regression subspaces [Details]