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
Gayle Leen
  • ESANN 2006 - A Gaussian process latent variable model formulation of canonical correlation analysis [Details]
  • ESANN 2006 - Stochastic Processes for Canonical Correlation Analysis [Details]
  • ESANN 2012 - Sparse Nonparametric Topic Model for Transfer Learning [Details]
D. Lefebvre
  • ESANN 2003 - Autonomous learning algorithm for fully connected recurrent networks [Details]
Dimitri Lefebvre
  • ESANN 2008 - Petri nets design based on neural networks [Details]
  • ESANN 2009 - Self-organising map for large scale processes monitoring [Details]
Augustin Lefèvre
  • ESANN 2013 - A nuclear-norm based convex formulation for informed source separation [Details]
Sébastien Lefèvre
  • ESANN 2016 - A new penalisation term for image retrieval in clique neural networks [Details]
Mathieu Lefort
  • ESANN 2014 - Discrimination of visual pedestrians data by combining projection and prediction learning [Details]
  • ESANN 2015 - Resource-efficient Incremental learning in very high dimensions [Details]
  • ESANN 2015 - Using self-organizing maps for regression: the importance of the output function [Details]
J.D. Legat
  • ESANN 1993 - Optimal decision surfaces in LVQ1 classiffication of patterns [Details]
  • ESANN 1995 - Suboptimal Bayesian classification by vector quantization with small clusters [Details]
P. Lehtimäki
  • ESANN 2002 - Mobile radio access network monitoring using the self-organizing map [Details]
Pasi Lehtimäki
  • ESANN 2006 - Hierarchical analysis of GSM network performance data [Details]
M. Lehtokangas
  • ESANN 1995 - Simplified cascade-correlation learning [Details]
  • ESANN 1996 - Maximum covariance method for weight initialization of multilayer perceptron network [Details]
  • ESANN 2003 - On radial basis function network equalization in the GSM system [Details]
David Leins
  • ESANN 2024 - Visualizing and Improving 3D Mesh Segmentation with DeepView [Details]
G.L. Leinsinger
  • ESANN 2001 - Analysis of dynamic perfusion MRI data by neural networks [Details]
A.P. Leitão
  • ESANN 2003 - Road Singularities Detection and Classification [Details]
Plinio Leitao-Junior
  • ESANN 2018 - Evolutionary Composition of Customized Fault Localization Heuristics [Details]
Cristiano Leite de Castro
  • ESANN 2024 - Unsupervised Drift Detection Using Quadtree Spatial Mapping [Details]
Douglas Leith
  • ESANN 2022 - High Accuracy and Low Regret for User-Cold-Start Using Latent Bandits [Details]
  • ESANN 2025 - Improving Privacy Benefits of Redaction [Details]
Douglas Leith
  • No papers found
Kauko Leiviskä
  • No papers found
Nicolas Lejeune
  • ESANN 2019 - Tensor factorization to extract patterns in multimodal EEG data [Details]
Simon Lejoly
  • ESANN 2024 - Extrapolating Venusian Atmospheric Profiles using MAGMA Gaussian Processes [Details]
Corinne Lejus-Bourdeau
  • ESANN 2024 - LSTM encoder-decoder model for contextualized time series forecasting applied to the simulation of a digital patient's physiological variables. [Details]
Corinne Lejus-Bourdeau
  • ESANN 2023 - A hidden Markov model with Hawkes process-derived contextual variables to improve time series prediction. Case study in medical simulation. [Details]
  • ESANN 2025 - Investigating four deep learning approaches as candidates for unified models in time series forecasting and event prediction: application in anesthesia training [Details]
Rupendra Lekkala
  • ESANN 2026 - The Alignment Gate: Intent and Instruction Guardrails for Agentic AI [Details]
S. Lelandais
  • ESANN 2003 - Road Singularities Detection and Classification [Details]
Jan Lemeire
  • ESANN 2011 - Inferring the causal decomposition under the presence of deterministic relations [Details]
Christiane Lemke
  • ESANN 2008 - Do we need experts for time series forecasting? [Details]
S. Lemm
  • ESANN 1999 - Hidden Markov gating for prediction of change points in switching dynamical systems [Details]
Andre Lemme
  • ESANN 2010 - Efficient online learning of a non-negative sparse autoencoder [Details]
  • ESANN 2012 - Learning visuo-motor coordination for pointing without depth calculation [Details]
  • ESANN 2013 - Neurally imprinted stable vector fields [Details]
  • ESANN 2015 - A flat neural network architecture to represent movement primitives with integrated sequencing [Details]
André P. Lemos
  • ESANN 2014 - A new approach for multiple instance learning based on a homogeneity bag operator [Details]
  • ESANN 2014 - Parameter-free regularization in Extreme Learning Machines with affinity matrices [Details]
Andre Lemos
  • ESANN 2015 - An affinity matrix approach for structure selection of extreme learning machines [Details]