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
Raphaël Puget
  • ESANN 2020 - Time Series Prediction using Disentangled Latent Factors [Details]
Matthieu Puigt
  • ESANN 2006 - A time-scale correlation-based blind separation method applicable to correlated sources [Details]
  • ESANN 2014 - Enhanced NMF initialization using a physical model for pollution source apportionment [Details]
  • ESANN 2017 - Environmental signal processing: new trends and applications [Details]
C.G. Puntonet
  • ESANN 1998 - Separation of sources in a class of post-nonlinear mixtures [Details]
  • ESANN 2001 - A stochastic and competitive network for the separation of sources [Details]
  • ESANN 2001 - The synergy between multideme genetic algorithms and fuzzy systems [Details]
  • ESANN 2002 - Orthogonal transformations for optimal time series prediction [Details]
C. G. Puntonet
  • ESANN 2003 - Neural Net with Two Hidden Layers for Non-Linear Blind Source Separation [Details]
Carlos G. Puntonet
  • ESANN 2004 - ON-LINE SUPPORT VECTOR MACHINES AND OPTIMIZATION STRATEGIES [Details]
Tuomas Puoliväli
  • ESANN 2013 - Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis [Details]
J.M. Pupo
  • ESANN 2000 - Neurocontrol of a binary distillation column [Details]
James Pustejovsky
  • ESANN 2017 - Fine-grained event learning of human-object interaction with LSTM-CRF [Details]
Evgeny Putin
  • ESANN 2018 - Pollen grain recognition using convolutional neural network [Details]
Jari Puttonen
  • ESANN 2015 - Prediction of concrete carbonation depth using decision trees [Details]
Felix Putze
  • ESANN 2018 - behaviour-based working memory capacity classification using recurrent neural networks [Details]
D. Puzenat
  • ESANN 2002 - Neural networks for modeling memory : case studies [Details]
Didier Puzenat
  • ESANN 2012 - Real time drunkenness analysis in a realistic car simulation [Details]
  • ESANN 2013 - Multi-user Blood Alcohol Content estimation in a realistic simulator using Artificial Neural Networks and Support Vector Machines [Details]
Alexander Pysik
  • ESANN 2019 - Machine learning in research and development of new vaccines products: opportunities and challenges [Details]
Eduardo J. P\'aez
  • ESANN 2020 - Machine learning framework for control in classical and quantum domains [Details]