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
Andrea Cossu
  • ESANN 2021 - Continual Learning with Echo State Networks [Details]
  • ESANN 2022 - Continual Learning for Human State Monitoring [Details]
  • ESANN 2023 - A Protocol for Continual Explanation of SHAP [Details]
Nuno Costa
  • ESANN 2024 - Leveraging Physics-Informed Neural Networks as Solar Wind Forecasting Models [Details]
Fabrizio Costa
  • ESANN 2016 - RNAsynth: constraints learning for RNA inverse folding. [Details]
  • ESANN 2017 - Fast hyperparameter selection for graph kernels via subsampling and multiple kernel learning [Details]
  • ESANN 2017 - The Conjunctive Disjunctive Node Kernel [Details]
  • ESANN 2019 - Progress Towards Graph Optimization: Efficient Learning of Vector to Graph Space Mappings [Details]
F. Costa
  • ESANN 1999 - A topological transformation for hidden recursive modelsarchitecture networks [Details]
Marcelo Costa
  • 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]
  • ESANN 2015 - Training Multi-Layer Perceptron with Multi-Objective Optimization and Spherical Weights Representation [Details]
M. Costa
  • ESANN 1994 - Combining multi-layer perceptrons in classification problems [Details]
Marta Costa-jussa
  • ESANN 2017 - Bridging deep and kernel methods [Details]
Filippo Costanti
  • ESANN 2022 - A Deep Learning approach for oocytes segmentation and analysis [Details]
Filippo Costanti
  • No papers found
Yannis Cotronis
  • ESANN 2017 - A Deep Q-Learning Agent for L-Game with Variable Batch Training [Details]
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]
M. Cottrell
  • ESANN 1993 - Time series and neural: a statistical method for weight elimination [Details]
  • ESANN 1994 - Two or three things that we know about the Kohonen algorithm [Details]
  • ESANN 1995 - Multiple correspondence analysis of a crosstabulations matrix using the Kohonen algorithm [Details]
  • ESANN 1996 - A Kohonen map representation to avoid misleading interpretations [Details]
  • ESANN 1997 - Kohonen maps versus vector quantization for data analysis [Details]
  • ESANN 1997 - New criterion of identification in the multilayered perceptron modelling [Details]
  • ESANN 1997 - Self organizing map for adaptive non-stationary clustering: some experimental results on color quantization of image sequences [Details]
  • ESANN 1998 - Forecasting time-series by Kohonen classification [Details]
  • ESANN 1999 - Using the Kohonen algorithm for quick initialization of Simple Competitive Learning algorithm [Details]
  • ESANN 2000 - Bootstrap for neural model selection [Details]
  • ESANN 2000 - Bootstrapping Self-Organizing Maps to assess the statistical significance of local proximity [Details]
  • ESANN 2001 - Some known facts about financial data [Details]
  • ESANN 2002 - Advantages and drawbacks of the Batch Kohonen algorithm [Details]
  • ESANN 2003 - Analyzing surveys using the Kohonen algorithm [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]
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
  • ESANN 2022 - Anomaly detections on the oil system of a turbofan engine by a neural autoencoder [Details]
Jean Coussirou
  • No papers found
Anthony Coutant
  • ESANN 2021 - Multivariate Time Series Multi-Coclustering. Application to Advanced Driving Assistance System Validation [Details]
Anthony Coutant
  • ESANN 2015 - On the equivalence between regularized NMF and similarity-augmented graph partitioning [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]