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
Denis Rousselle
  • ESANN 2015 - Optimal transport for semi-supervised domain adaptation [Details]
P. Rousset
  • ESANN 2000 - Curve forecast with the SOM algorithm: using a tool to follow the time on a Kohonen map [Details]
Roman Rouzier
  • ESANN 2008 - A new method of DNA probes selection and its use with multi-objective neural network for predicting the outcome of breast cancer preoperative chemotherapy [Details]
Manuel Roveri
  • ESANN 2024 - An Efficient Neural Architecture Search Model for Medical Image Classification [Details]
S. Rovetta
  • ESANN 1995 - Learning the appropriate representation paradigm by circular processing units [Details]
Xavier Rovira
  • ESANN 2011 - A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences [Details]
George Rovithakis
  • ESANN 2004 - reduced dimensionality space for post placement quality inspection of components based on neural networks [Details]
G. Rovithakis
  • ESANN 2001 - A structural genetic algorithm to optimize High Order Neural Network architecture [Details]
Liang Ru-Ze
  • ESANN 2017 - Learning convolutional neural network to maximize Pos@Top performance measure [Details]
J. Ruan
  • ESANN 1997 - Nonlinearity and separation capability: further justification for the ICA algorithm with a learned mixture of parametric densities [Details]
Gerardo Rubino
  • ESANN 2024 - Exploring Self-Organizing Maps for Addressing Semantic Impairments [Details]
Gines Rubio
  • ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
U. Rückert
  • ESANN 2002 - A reconfigurable SOM hardware accelerator [Details]
Ulrich Rückert
  • ESANN 2006 - Robust Local Cluster Neural Networks [Details]
  • ESANN 2007 - Controlling complexity of RBF networks by similarity [Details]
  • ESANN 2012 - Hardware accelerated real time classification of hyperspectral imaging data for coffee sorting [Details]
  • ESANN 2012 - Parallel neural hardware: the time is right [Details]
  • ESANN 2012 - gNBXe -- a Reconfigurable Neuroprocessor for Various Types of Self-Organizing Maps [Details]
Théo Rudkiewicz
  • ESANN 2025 - Growth strategies for arbitrary DAG neural architectures [Details]
B. Ruf
  • ESANN 1994 - A stop criterion for the Boltzmann machine learning algorithm [Details]
Cyprien Ruffino
  • ESANN 2019 - Pixel-wise Conditioning of Generative Adversarial Networks [Details]
S.M. Rüger
  • ESANN 1996 - An analysis of the metric structure of the weight space of feedforward networks and its application to time series modeling and prediction [Details]
Francisco J. Ruiz
  • ESANN 2009 - SVM-based learning method for improving colour adjustment in automotive basecoat manufacturing [Details]
Héctor Ruiz
  • ESANN 2011 - The role of Fisher information in primary data space for neighbourhood mapping [Details]
  • ESANN 2012 - Constructing similarity networks using the Fisher information metric [Details]
  • ESANN 2015 - Measuring scoring efficiency through goal expectancy estimation [Details]
Juan Carlos Ruiz-Rodríguez
  • ESANN 2013 - A quotient basis kernel for the prediction of mortality in severe sepsis patients [Details]
Thomas Runkler
  • ESANN 2021 - Behavior Constraining in Weight Space for Offline Reinforcement Learning [Details]
  • ESANN 2021 - Differentially Private Time Series Generation [Details]
  • ESANN 2023 - Automatic Trade-off Adaptation in Offline RL [Details]
  • ESANN 2025 - Is Q-learning an Ill-posed Problem? [Details]
  • ESANN 2025 - TEA: Trajectory Encoding Augmentation for Robust and Transferable Policies in Offline Reinforcement Learning [Details]
Thomas Runkler
  • ESANN 2014 - Exploiting similarity in system identification tasks with recurrent neural networks [Details]
  • ESANN 2018 - Sensitivity analysis for predictive uncertainty [Details]
  • ESANN 2019 - interpretable dynamics models for data-efficient reinforcement learning [Details]
María J. Rupérez-Moreno
  • ESANN 2020 - Cost-free resolution enhancement in Convolutional Neural Networks for medical image segmentation [Details]
S. Rushton
  • ESANN 1999 - Regularization in oculomotor adaptation [Details]
Nicola Russo
  • ESANN 2023 - Pattern Recognition Spiking Neural Network for Classification of Chinese Characters [Details]
Alistair G. Rust
  • ESANN 2006 - Using sampling methods to improve binding site predictions [Details]
David Ruttens
  • ESANN 2025 - Exploring Model Architectures for Real-Time Lung Sound Event Detection [Details]
Dawid Rymarczyk
  • ESANN 2024 - ProtoNCD: Prototypical Parts for Interpretable Novel Class Discovery [Details]
joseph Rynkiewicz
  • ESANN 2005 - efficient estimation of multidimensional regression model with multilayer perceptron [Details]
  • ESANN 2006 - Consistent estimation of the architecture of multilayer perceptrons [Details]
  • ESANN 2007 - Estimating the Number of Components in a Mixture of Multilayer Perceptrons [Details]
  • ESANN 2010 - Asymptotic properties of mixture-of-experts models [Details]
  • ESANN 2011 - General bound of overfitting for MLP regression models [Details]
  • ESANN 2012 - Quantile regression with multilayer perceptrons. [Details]
  • ESANN 2018 - Asymptotic statistics for multilayer perceptron with ReLu hidden units [Details]
  • ESANN 2019 - On overfitting of multilayer perceptrons for classification [Details]