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
Philippe Gorce
  • ESANN 2005 - Using generic neural networks in the control and prediction of grasp postures [Details]
M. B. Gordon
  • ESANN 1995 - An evolutive architecture coupled with optimal perceptron learning for classification [Details]
  • ESANN 1997 - Numerical simulations of an optimal algorithm for supervised learning [Details]
M. Gordon
  • ESANN 1999 - Detection of two Gaussian clusters [Details]
  • ESANN 1999 - Statistical mechanics of support vector machine [Details]
M.B. Gordon
  • ESANN 1993 - Minimerror: a perceptron learning rule that finds the optimal weights [Details]
Agnès Gorge
  • ESANN 2004 - Computational model of amygdala network supported by neurobiological data [Details]
Kyller Gorgônio
  • ESANN 2026 - On the Impact of Differential Privacy on Federated Neuromorphic Learning Accuracy [Details]
Marco Gori
  • ESANN 2016 - Learning with hard constraints as a limit case of learning with soft constraints [Details]
M. Gori
  • ESANN 1999 - Learning in structured domains [Details]
  • ESANN 1999 - Neural learning of approximate simple regular languages [Details]
  • ESANN 2001 - Searching the Web: learning based techniques [Details]
  • ESANN 2003 - An introduction to learning in web domains [Details]
Marco Gori
  • ESANN 2025 - Stability of State and Costate Dynamics in Continuous Time Recurrent Neural Networks [Details]
Dirk Gorissen
  • ESANN 2007 - Adaptive Global Metamodeling with Neural Networks [Details]
Juan Manuel Gorriz
  • ESANN 2004 - ON-LINE SUPPORT VECTOR MACHINES AND OPTIMIZATION STRATEGIES [Details]
Denise Gorse
  • ESANN 2011 - Application of stochastic recurrent reinforcement learning to index trading [Details]
  • ESANN 2013 - Binary particle swarm optimisation with improved scaling behaviour [Details]
  • ESANN 2017 - Pseudo-analytical solutions for stochastic options pricing using Monte Carlo simulation and Breeding PSO-trained neural networks [Details]
  • ESANN 2018 - A neural network cost function for highly class-imbalanced data sets [Details]
  • ESANN 2018 - Reinforcement Learning for High-Frequency Market Making [Details]
D. Gorse
  • ESANN 1993 - Traking global minima using a range expansion algorithm [Details]
K. Goser
  • ESANN 1993 - Three algorithms for searching the minimum distance in the self-organizing maps [Details]
  • ESANN 1994 - Self-organizing maps based on differential equations [Details]
Philippe-Henri Gosselin
  • ESANN 2012 - Linear kernel combination using boosting [Details]
  • ESANN 2013 - Machine Learning and Content-Based Multimedia Retrieval [Details]
  • ESANN 2014 - Dimensionality reduction in decentralized networks by Gossip aggregation of principal components analyzers [Details]
  • ESANN 2015 - Asynchronous decentralized convex optimization through short-term gradient averaging [Details]
Bernard Gosselin
  • No papers found
Bernard Gosselin
  • ESANN 2022 - Semi-synthetic Data for Automatic Drone Shadow Detection [Details]
E. Gotko
  • ESANN 1998 - Ultrasound medical image processing using cellular neural networks [Details]
Michael Götting
  • ESANN 2006 - Adaptive scene-dependent filters in online learning environments [Details]
Hanno Gottschalk
  • ESANN 2025 - Robust Evolutionary Multi-Objective Neural Architecture Search for Reinforcement Learning (EMNAS-RL) [Details]
Stefanos Goumas
  • ESANN 2004 - reduced dimensionality space for post placement quality inspection of components based on neural networks [Details]
Benoit Goupil
  • ESANN 2026 - GNNs Don't Need Backprop [Details]
Pierre-Yves Gousenbourger
  • ESANN 2016 - Differentiable piecewise-Bézier interpolation on Riemannian manifolds [Details]
  • ESANN 2017 - Piecewise-Bézier C1 smoothing on manifolds with application to wind field estimation [Details]
  • ESANN 2019 - Interpolation on the manifold of fixed-rank positive-semidefinite matrices for parametric model order reduction: preliminary results [Details]
Cédric Gouy-Pailler
  • ESANN 2009 - Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics [Details]
  • ESANN 2012 - From neuronal cost-based metrics towards sparse coded signals classification [Details]
Gérard Govaert
  • ESANN 2007 - Learning topology of a labeled data set with the supervised generative gaussian graph [Details]
  • ESANN 2009 - A regression model with a hidden logistic process for signal parametrization [Details]
  • ESANN 2012 - A generative model that learns Betti numbers from a data set [Details]
  • ESANN 2013 - Clustering the Vélib’ origin-destinations flows by means of Poisson mixture models [Details]
Ekaterina Govorkova
  • ESANN 2023 - Knowledge Distillation for Anomaly Detection [Details]
K. Grabczewski
  • ESANN 1997 - Extraction of crisp logical rules using constrained backpropagation networks [Details]
I. Grabec
  • ESANN 1995 - Function approximation by localized basis function neural network [Details]
  • ESANN 1997 - Equivalence of a radial basis function NN and a perceptron [Details]
Igor Grabec
  • No papers found
Torben Graeber
  • ESANN 2021 - AGLVQ - Making Generalized Vector Quantization Algorithms Aware of Context [Details]