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
Marie Cottrell
  • ESANN 2010 - Self Organizing Star (SOS) for health monitoring [Details]
  • ESANN 2012 - Robust clustering of high-dimensional data [Details]
  • ESANN 2015 - Search Strategies for Binary Feature Selection for a Naive Bayes Classifier [Details]
Miguel Couceiro
  • ESANN 2024 - Clarity: a Deep Ensemble for Visual Counterfactual Explanations [Details]
Rémi Coulom
  • ESANN 2004 - high-accuracy value-function approximation with neural networks applied to the acrobot [Details]
Elizabeth Coulthard
  • ESANN 2025 - Direct versus intermediate multi-task transfer learning for dementia detection from unstructured conversations [Details]
Patty Coupeau
  • ESANN 2025 - Multi-View Graph Neural Network for Image Segmentation : Intermediate vs Late Fusion [Details]
Edouard Couplet
  • 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]
  • ESANN 2025 - Can MDS rival with t-SNE by using the symmetric Kullback-Leibler divergence\\ across neighborhoods as a pseudo-distance? [Details]
  • ESANN 2026 - Interpretable Parametric Neighbour Embedding [Details]
  • ESANN 2026 - Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths [Details]
Dominique Courcot
  • ESANN 2014 - Enhanced NMF initialization using a physical model for pollution source apportionment [Details]
Nicolas Courty
  • ESANN 2016 - A new penalisation term for image retrieval in clique neural networks [Details]
Aaron Courville
  • ESANN 2016 - Deep Learning Vector Quantization [Details]
Jean Coussirou
  • No papers found
Jean Coussirou
  • ESANN 2022 - Anomaly detections on the oil system of a turbofan engine by a neural autoencoder [Details]
Anthony Coutant
  • ESANN 2015 - On the equivalence between regularized NMF and similarity-augmented graph partitioning [Details]
Anthony Coutant
  • ESANN 2021 - Multivariate Time Series Multi-Coclustering. Application to Advanced Driving Assistance System Validation [Details]
Paulo Coutinho
  • ESANN 2014 - Extracting rules from DRASiW’s "mental images" [Details]
C. Couvreur
  • ESANN 1995 - MAP decomposition of a mixture of AR signal using multilayer perceptrons [Details]
Glen Cowan
  • ESANN 2016 - How machine learning won the Higgs boson challenge [Details]
Laura Cozzi
  • ESANN 2006 - Cultures of dissociated neurons display a variety of avalanche behaviours [Details]
David Crawford
  • No papers found
Francesco Crecchi
  • ESANN 2020 - Perplexity-free Parametric t-SNE [Details]
Francesco Crecchi
  • ESANN 2019 - Detecting Black-box Adversarial Examples through Nonlinear Dimensionality Reduction [Details]
B. Crespi
  • ESANN 1999 - Storage capacity and dynamics of nonmonotonic networks [Details]
J.L. Crespo
  • ESANN 2000 - Using higher order synapses and nodes to improve sensing capabilities of mobile robots [Details]
Guillaume Crevecoeur
  • ESANN 2025 - Efficient Training of Neural SDEs Using Stochastic Optimal Control [Details]
Perrine Cribier-Delande
  • ESANN 2020 - Time Series Prediction using Disentangled Latent Factors [Details]
N. Cristianini
  • ESANN 1999 - A multiplicative updating algorithm for training support vector machine [Details]
Joana Cristo Santos
  • ESANN 2024 - Reconstruction of Mammography Projections using Image-to-Image Translation Techniques [Details]
Joana Cristo Santos
  • ESANN 2020 - Missing Image Data Imputation using Variational Autoencoders with Weighted Loss [Details]
Matthew W. Crocker
  • ESANN 2007 - Systematicity in sentence processing with a recursive self-organizing neural network [Details]
Nigel Crook
  • ESANN 2004 - a chaotic basis for neural coding [Details]
  • ESANN 2005 - The Nonlinear Dynamic State neuron [Details]
  • ESANN 2006 - Nonlinear dynamics in neural computation [Details]
  • ESANN 2006 - Nonlinear transient computation and variable noise tolerance [Details]
  • ESANN 2007 - Human motion recognition using Nonlinear Transient Computation [Details]
  • ESANN 2007 - Pattern Recognition using Chaotic Transients [Details]
Nigel Crook
  • ESANN 2023 - Efficient Learning in Spiking Models [Details]
  • ESANN 2023 - Functional Resonant Synaptic Clusters for Decoding Time-Structured Spike Trains [Details]