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
S. Cohen
  • ESANN 2003 - Ensemble of hybrid networks with strong regularization [Details]
Sarel Cohen
  • ESANN 2024 - Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange [Details]
Valentina Colla
  • ESANN 2021 - Echo-state neural networks forecasting steelworks off-gases for their dispatching in CH4 and CH3OH syntheses reactors [Details]
Valentina Colla
  • ESANN 2004 - comparison of different classification methods on castabilty data coming from steelmaking practice [Details]
Valentina Colla
  • ESANN 2004 - meaningful discretization of continuous features for association rules mining by means of a SOM [Details]
V. Colla
  • ESANN 1998 - A comparison between weighted radial basis functions and wavelet networks [Details]
  • ESANN 1998 - A neural approach to a sensor fusion problem [Details]
  • ESANN 1999 - Neuro-wavelet parametric characterization of hardness profiles [Details]
  • ESANN 1999 - Orthogonal least square algorithm applied to the initialization of multi-layer perceptrons [Details]
  • ESANN 2000 - Training activation function in parametric classification [Details]
  • ESANN 2003 - Comparison of traditional and neural systems for train speed estimation [Details]
Leandro Collier
  • ESANN 2025 - SecureBFL: a Blockchain-enhanced federated learning architecture with MPC [Details]
Anne-Sophie Collin
  • ESANN 2023 - Don't skip the skips: autoencoder skip connections improve latent representation discrepancy for anomaly detection [Details]
Greg Collinge
  • ESANN 2019 - Defending against poisoning attacks in online learning settings [Details]
Michele Colombo
  • ESANN 2017 - ELM Preference Learning for Physiological Data [Details]
C. Comaniciu
  • ESANN 1996 - Fast signal recognition and detection using ART1 neural networks and nonlinear preprocessing units based on time delay embeddings [Details]
Etienne Come
  • ESANN 2021 - A Lightweight Approach for Origin-Destination Matrix Anonymization [Details]
  • ESANN 2021 - Machine learning and data mining for urban mobility intelligence [Details]
Etienne Côme
  • ESANN 2009 - Partially-supervised learning in Independent Factor Analysis [Details]
  • ESANN 2010 - Self Organizing Star (SOS) for health monitoring [Details]
  • ESANN 2013 - Clustering the Vélib’ origin-destinations flows by means of Poisson mixture models [Details]
  • ESANN 2013 - Hierarchical and multiscale Mean Shift segmentation of population grids [Details]
  • ESANN 2017 - Multiscale Spatio-Temporal Data Aggregation and Mapping for Urban Data Exploration [Details]
  • ESANN 2017 - Processing, mining and visualizing massive urban data [Details]
P. Comon
  • ESANN 1994 - Estimation of performance bounds in supervised classification [Details]
  • ESANN 1995 - Invited paper: Supervised classification: a probabilistic approach [Details]
Brieuc Conan-Guez
  • ESANN 2004 - Clustering functional data with the SOM algorithm [Details]
  • ESANN 2012 - Dissimilarity Clustering by Hierarchical Multi-Level Refinement [Details]
  • ESANN 2018 - K-spectral centroid: extension and optimizations [Details]
Brieuc Conan-Guez
  • ESANN 2024 - Clarity: a Deep Ensemble for Visual Counterfactual Explanations [Details]
Brieuc Conan-Guez
  • ESANN 2004 - functional radial basis function networks [Details]
Brieuc Conan-Guez
  • ESANN 2004 - Functional preprocessing for multilayer perceptrons [Details]
B. Conan-Guez
  • ESANN 2002 - Theoretical properties of functional Multi Layer Perceptrons [Details]
Robin Condat
  • ESANN 2020 - Random Signal Cut for Improving Multimodal CNN Robustness of 2D Road Object Detection [Details]
Alexandru Paul Condurache
  • ESANN 2020 - GraN: An Efficient Gradient-Norm Based Detector for Adversarial and Misclassified Examples [Details]
  • ESANN 2020 - Invariant Integration in Deep Convolutional Feature Space [Details]
Fengyu Cong
  • ESANN 2013 - Dimension reduction for individual ica to decompose FMRI during real-world experiences: principal component analysis vs. canonical correlation analysis [Details]
Marco Congedo
  • ESANN 2009 - Uncued brain-computer interfaces: a variational hidden markov model of mental state dynamics [Details]
  • ESANN 2011 - Identification of sparse spatio-temporal features in Evoked Response Potentials [Details]
  • ESANN 2012 - BCI Signal Classification using a Riemannian-based kernel [Details]
  • ESANN 2012 - The error-related potential and BCIs [Details]
  • ESANN 2016 - Unsupervised Cross-Subject BCI Learning and Classification using Riemannian Geometry [Details]
T. Conradi
  • ESANN 1999 - Critical and non-critical avalanche behavior in networks of integrate-and-fire neurons [Details]
Jörg Conradt
  • ESANN 2018 - Towards cognitive automotive environment modelling: reasoning based on vector representations [Details]
  • ESANN 2019 - Predicting vehicle behaviour using LSTMs and a vector power representation for spatial positions [Details]
  • ESANN 2019 - Short-term trajectory planning using reinforcement learning within a neuromorphic control architecture [Details]
Jörg Conradt
  • ESANN 2020 - Detection of abnormal driving situations using distributed representations and unsupervised learning [Details]
Gabriella Contardo
  • ESANN 2016 - Learning Embeddings for Completion and Prediction of Relationnal Multivariate Time-Series [Details]
M. Conti
  • ESANN 1995 - Analog Brownian weight movement for learning of artificial neural networks [Details]
Felipe Contreras
  • ESANN 2023 - Improved the locally aligned ant technique (LAAT) strategy to recover manifolds embedded in strong noise [Details]
  • ESANN 2025 - Adaptive Locally Aligned Ant Technique for Manifold Detection and Denoising [Details]
Pedro Jesús Copado
  • ESANN 2025 - Altered emotion recognition from psychiatric patient profiles using Machine Learning [Details]