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
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 - 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]
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]
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]
Mauro Conti
  • ESANN 2026 - Model Selection Hijacking Adversarial Attack [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]
Felipe Contreras
  • ESANN 2026 - Hub-Aware Hybrid Search: Accelerating the Locally Aligned Ant Technique [Details]
Pedro Jesús Copado
  • ESANN 2025 - Altered emotion recognition from psychiatric patient profiles using Machine Learning [Details]
  • ESANN 2026 - Techniques for Reliable, Safe and Robust AI Applications [Details]
M. Copelli
  • ESANN 1997 - Noise robustness in the perceptron [Details]
Gilles Coppin
  • ESANN 2024 - Invariant Representation Learning for Generalizable Imitation [Details]
Andrea Coraddu
  • ESANN 2025 - Reconciling Grokking with Statistical Learning Theory [Details]
Marilys Corbex
  • ESANN 2008 - Handling almost-deterministic relationships in constraint-based Bayesian network discovery : Application to cancer risk factor identification [Details]
A. Corbi
  • ESANN 1999 - Neural learning of approximate simple regular languages [Details]
Sacha Corbugy
  • ESANN 2024 - Insight-SNE: Understanding t-SNE Embeddings through Interactive Explanation [Details]
E. Corchado
  • ESANN 2001 - Rectified Gaussian distributions and the formation of local filters from video data [Details]
  • ESANN 2002 - Maximum likelihood Hebbian rules [Details]
Matthieu Cord
  • ESANN 2012 - Learning geometric combinations of Gaussian kernels with alternating Quasi-Newton algorithm [Details]
L. Corleto
  • ESANN 1996 - Error rate estimation via cross-validation and learning curve theory [Details]
Marco Corneli
  • No papers found
Marco Corneli
  • ESANN 2023 - Deep dynamic co-clustering of streams of count data: a new online Zip-dLBM [Details]