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
Magda Friedjungová
  • ESANN 2020 - Unsupervised Latent Space Translation Network [Details]
Jan Friedland
  • ESANN 2008 - Learning to play Tetris applying reinforcement learning methods [Details]
F. Friedrich
  • ESANN 2000 - A neuro-fuzzy approach as medical diagnostic interface [Details]
Tobias Friedrich
  • ESANN 2024 - Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange [Details]
Klaus Friedrichs
  • ESANN 2019 - Fast and reliable architecture selection for convolutional neural networks [Details]
Frauke Friedrichs
  • ESANN 2004 - Evolutionary tuning of multiple SVM parameters [Details]
T. Friess
  • ESANN 1999 - A kernel based adaline [Details]
Jannik Fritsch
  • ESANN 2008 - Computationally Efficient Neural Field Dynamics [Details]
J. Fritsch
  • ESANN 1998 - Hierarchies of neural networks for connectionist speech recognition [Details]
B. Fritzke
  • ESANN 1996 - Growing self-organizing networks - Why ? [Details]
A.A. Frolov
  • ESANN 1993 - Once more on the information capacity of the hopefield network [Details]
  • ESANN 1999 - Nonlinear factorization in sparsely encoded Hopfield-like neural networks [Details]
Pascal Frossard
  • ESANN 2017 - Learning sparse models of diffusive graph signals [Details]
Robert Frouin
  • ESANN 2004 - On fields of nonlinear regression models [Details]
J.M. Fuertes
  • ESANN 1994 - Capabilities of a structured neural network. Learning and comparison with classical techniques [Details]
Robert Fujii
  • ESANN 2004 - input arrival-time-dependent decoding scheme for a spiking neural network [Details]
Kaori Fujita
  • ESANN 2009 - Comparison between linear discrimination analysis and support vector machine for detection of pesticide on spinach leaf by hyperspectral imaging with excitation-emission matrix [Details]
Fabian Fumagalli
  • ESANN 2023 - On Feature Removal for Explainability in Dynamic Environments [Details]
  • ESANN 2025 - Explaining Outliers using Isolation Forest and Shapley Interactions [Details]
Y. Funahashi
  • ESANN 1995 - On the function of the retinal bipolar cell in early vision [Details]
Mathias Funk
  • ESANN 2015 - Advances in learning analytics and educational data mining [Details]
  • ESANN 2015 - Human Algorithmic Stability and Human Rademacher Complexity [Details]
Johannes Fürnkranz
  • ESANN 2009 - Efficient voting prediction for pairwise multilabel classification [Details]
  • ESANN 2016 - Using semantic similarity for multi-label zero-shot classification of text documents [Details]
  • ESANN 2019 - Beta Distribution Drift Detection for Adaptive Classifiers [Details]
Angelo Furno
  • ESANN 2021 - A Lightweight Approach for Origin-Destination Matrix Anonymization [Details]
  • ESANN 2021 - Unsupervised Real-time Anomaly Detection for Multivariate Mobile Phone Traffic Series [Details]
Junya Furuki
  • ESANN 2025 - Sleep Staging with Gradient Boosting and DWT-PSD Features from EEG/EOG Signals [Details]
C. Fyfe
  • ESANN 1997 - Independence is far from normal [Details]
  • ESANN 1998 - Canonical correlation analysis using artificial neural networks [Details]
  • ESANN 1998 - Invariant feature maps for analysis of orientations in image data [Details]
  • ESANN 1999 - Comparison of Kohonen, scale-invariant and GTM self-organising maps for interpretation of spectral data [Details]
  • ESANN 1999 - Neural networks which identify composite factors [Details]
  • ESANN 1999 - Noise to extract independent causes [Details]
  • ESANN 1999 - Trends in Unsupervised Learning [Details]
  • ESANN 2001 - Rectified Gaussian distributions and the formation of local filters from video data [Details]
  • ESANN 2001 - Sparse Kernel Canonical Correlation Analysis [Details]
  • ESANN 2001 - Unsupervised models for processing visual data [Details]
  • ESANN 2002 - Clustering in data space and feature space [Details]
  • ESANN 2002 - Exploratory Correlation Analysis [Details]
  • ESANN 2002 - Forecasting using twinned principal curves [Details]
  • ESANN 2002 - Maximum likelihood Hebbian rules [Details]
Colin Fyfe
  • ESANN 2004 - Using Andrews Curves for Clustering and Sub-clustering Self-Organizing Maps [Details]
  • ESANN 2005 - Phase transition in sparse associative neural networks [Details]
  • ESANN 2006 - A Gaussian process latent variable model formulation of canonical correlation analysis [Details]
  • ESANN 2006 - Immune Network based Ensembles [Details]
  • ESANN 2006 - Outlier identification with the Harmonic Topographic Mapping [Details]
  • ESANN 2006 - Stochastic Processes for Canonical Correlation Analysis [Details]
  • ESANN 2007 - Immediate Reward Reinforcement Learning for Projective Kernel Methods [Details]
  • ESANN 2010 - Curvilinear component analysis and Bregman divergences [Details]