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
Lucas Lamata
  • ESANN 2020 - Quantum Machine Learning [Details]
  • ESANN 2023 - Quantum Artificial Intelligence: A tutorial [Details]
Dolores Lamb
  • ESANN 2005 - Computational models of intracytoplasmic sperm injection prognosis [Details]
  • No papers found
Pierre Lambert
  • ESANN 2021 - Impact of data subsamplings in Fast Multi-Scale Neighbor Embedding. [Details]
  • ESANN 2021 - Stochastic quartet approach for fast multidimensional scaling [Details]
  • ESANN 2023 - Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration [Details]
  • ESANN 2023 - On the number of latent representations in deep neural networks for tabular data [Details]
  • ESANN 2024 - Estimated neighbour sets and smoothed sampled global interactions are sufficient for a fast approximate tSNE. [Details]
  • ESANN 2024 - Forget early exaggeration in t-SNE: early hierarchization preserves global structure [Details]
Anne Lambert
  • No papers found
Anne Lambert
  • ESANN 2022 - Feature Compression Using Dynamic Switches in Multi-split CNNs [Details]
D. Lamberton
  • ESANN 1996 - On the critical points of the 1-dimensional competitive learning vector quantization algorithm [Details]
Jean-Charles Lamirel
  • ESANN 2006 - A new hyperbolic visualization method for displaying the results of a neural gas model: application to Webometrics [Details]
Golan Lampi
  • ESANN 2009 - SOM based methods in early fault detection of nuclear industry [Details]
J. Lampinen
  • ESANN 2000 - Analytical comparison of the Temporal Kohonen Map and the Recurrent Self Organizing Map [Details]
  • ESANN 2000 - Self-Organizing Maps in data analysis - notes on overfitting and overinterpretation [Details]
Yuan Lan
  • ESANN 2010 - Random search enhancement of error minimized extreme learning machine [Details]
Tian Lan
  • ESANN 2010 - Identifying informative features for ERP speller systems based on RSVP paradigm [Details]
N. Lanconelli
  • ESANN 2000 - Automatic detection of clustered microcalcifications in digital mammograms using an SVM classifier [Details]
Magdalena Landl
  • ESANN 2020 - 3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution [Details]
M. Lando
  • ESANN 2003 - Post-failure analysis of an adaptive predictor-corrector neural controller on a flight simulator [Details]
Francesco Landolfi
  • ESANN 2022 - Revisiting Edge Pooling in Graph Neural Networks [Details]
  • ESANN 2023 - A Tropical View of Graph Neural Networks [Details]
  • ESANN 2024 - Generalizing Convolution to Point Clouds [Details]
Francesco Landolfi
  • No papers found
E.W. Lang
  • ESANN 2002 - Geometric overcomplete ICA [Details]
  • ESANN 2002 - How to generalize geometric ICA to higher dimensions [Details]
Bernhard Lang
  • ESANN 2009 - Monotonic Recurrent Bounded Derivative Neural Network [Details]
Elmar Wolfgang Lang
  • ESANN 2004 - Lattice ICA for the separation of speech signals [Details]
Elmar Wolfgang Lang
  • ESANN 2004 - Linearization identification and an application to BSS using a SOM [Details]
Mandy Lange
  • ESANN 2012 - Modified Conn-Index for the evaluation of fuzzy clusterings [Details]
  • ESANN 2013 - Non-Euclidean independent component analysis and Oja's learning [Details]
  • ESANN 2014 - Applications of lp-Norms and their Smooth Approximations for Gradient Based Learning Vector Quantization [Details]
  • ESANN 2015 - Learning matrix quantization and variants of relevance learning [Details]
Sascha Lange
  • ESANN 2021 - Sample efficient localization and stage prediction with autoencoders [Details]
Sascha Lange
  • ESANN 2010 - Deep learning of visual control policies [Details]
  • ESANN 2017 - Predicting Time Series with Space-Time Convolutional and Recurrent Neural Networks [Details]
O. Lange
  • ESANN 2001 - Analysis of dynamic perfusion MRI data by neural networks [Details]
Markus Lange
  • ESANN 2024 - Robustness and Regularization in Hierarchical Re-Basin [Details]
Raphaël Langhendries
  • ESANN 2021 - Deep Learning Model for Context-Dependent Survival Analysis [Details]
Rocco Langone
  • ESANN 2015 - Ranking Overlap and Outlier Points in Data using Soft Kernel Spectral Clustering [Details]
  • ESANN 2016 - Clustering from two data sources using a kernel-based approach with weight coupling [Details]
  • ESANN 2016 - Fast in-memory spectral clustering using a fixed-size approach [Details]
Petr Lansky
  • ESANN 2012 - How regular is neuronal activity? [Details]
P. Lansky
  • ESANN 1994 - Stochastic model of odor intensity coding in first-order olfactory neurons [Details]
  • ESANN 1995 - Some new results on the coding of pheromone intensity in an olfactory sensory neuron [Details]