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
Barbara D. Wichtmann
  • ESANN 2024 - On the Stability of Neural Segmentation in Radiology [Details]
Stefan Wiegand
  • ESANN 2004 - Evolutionary Optimization of Neural Networks for Face Detection [Details]
Travis Wiens
  • ESANN 2007 - Algebraic inversion of an artificial neural network classifier [Details]
  • ESANN 2019 - Dimensionality reduction in a hydraulic valve positioning application [Details]
Marco Wiering
  • ESANN 2016 - Human detection and classification of landing sites for search and rescue drones [Details]
  • ESANN 2017 - Hyper-spectral frequency selection for the classification of vegetation diseases [Details]
  • ESANN 2017 - Support vector components analysis [Details]
Daan Wierstra
  • ESANN 2006 - Evolino for recurrent support vector machines [Details]
David Wild
  • ESANN 2004 - protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models [Details]
Jasper Wilfling
  • ESANN 2024 - Evaluating the Quality of Saliency Maps for Distilled Convolutional Neural Networks [Details]
S. Wilke
  • ESANN 1999 - What does a neuron talk about ? [Details]
S.D. Wilke
  • ESANN 2001 - Extracting motion information using a biologically realistic model retina [Details]
J. Wille
  • ESANN 1998 - A RNN based control architecture for generating periodic action sequences [Details]
Volker Willert
  • ESANN 2010 - Adaptive velocity tuning for visual motion estimation [Details]
  • ESANN 2012 - Unsupervised learning of motion patterns [Details]
  • ESANN 2013 - Learning associative spatiotemporal features with non-negative sparse coding [Details]
  • ESANN 2014 - Beyond histograms: why learned structure-preserving descriptors outperform HOG [Details]
D. Willett
  • ESANN 1998 - Speech recognition with a new hybrid architecture combining neural networks and continuous HMM [Details]
Heindel William
  • ESANN 2007 - Classifying n-back EEG data using entropy and mutual information features [Details]
A.I. Wilmer
  • ESANN 2001 - Texture analysis with the Volterra model using conjugate gradient optimisation [Details]
Campbell Wilson
  • ESANN 2024 - Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts [Details]
Martin Wimpff
  • ESANN 2024 - Towards calibration-free online EEG motor imagery decoding using Deep Learning [Details]
David Winant
  • ESANN 2025 - Generative Kernel Spectral Clustering [Details]
T. Windeatt
  • ESANN 1999 - AdaBoost and neural networks [Details]
Terry Windeatt
  • ESANN 2007 - Ensemble neural classifier design for face recognition [Details]
  • ESANN 2014 - Dynamic ensemble selection and instantaneous pruning for regression [Details]
  • ESANN 2015 - Ensemble Learning with Dynamic Ordered Pruning for Regression [Details]
O. Winther
  • ESANN 1997 - Bayesian online learning in the perceptron [Details]
Patrice Wira
  • ESANN 2005 - Adaline-based estimation of power harmonics [Details]
P. Wira
  • ESANN 2001 - A divide-and-conquer learning architecture for predicting unknown motion [Details]
  • ESANN 2003 - Neural networks organizations to learn complex robotic functions [Details]
Benedikt Wirth
  • ESANN 2016 - Differentiable piecewise-Bézier interpolation on Riemannian manifolds [Details]
Laurenz Wiskott
  • ESANN 2012 - An analysis of Gaussian-binary restricted Boltzmann machines for natural images [Details]
  • ESANN 2014 - Learning predictive partitions for continuous feature spaces [Details]
Laurenz Wiskott
  • ESANN 2024 - Antagonism between Classification and Reconstruction Processes in Deep Predictive Coding Networks [Details]
Axel Wismueller
  • ESANN 2009 - A computational framework for exploratory data analysis [Details]
  • ESANN 2009 - The Exploration Machine - a novel method for structure-preserving dimensionality reduction [Details]
Axel Wismueller
  • ESANN 2010 - Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization [Details]
  • ESANN 2010 - Recent Advances in Nonlinear Dimensionality Reduction, Manifold and Topological Learning [Details]
Axel Wismüller
  • ESANN 2004 - Theory and applications of neural maps [Details]
A. Wismüller
  • ESANN 2000 - A neural network approach to adaptive pattern analysis - the deformable feature map [Details]
  • ESANN 2001 - Analysis of dynamic perfusion MRI data by neural networks [Details]
  • ESANN 2002 - Exploratory Data Analysis in Medicine and Bioinformatics [Details]
  • ESANN 2003 - Digital Image Processing with Neural Networks [Details]
  • ESANN 2003 - Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis [Details]
Philipp Wissmann
  • ESANN 2024 - Why long model-based rollouts are no reason for bad Q-value estimates [Details]