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
Rima Guidara
  • ESANN 2007 - Markovian blind separation of non-stationary temporally correlated sources [Details]
Riccardo Guidotti
  • ESANN 2023 - A Protocol for Continual Explanation of SHAP [Details]
  • ESANN 2023 - Quantum Feature Selection with Variance Estimation [Details]
  • ESANN 2024 - Enhancing Echo State Networks with Gradient-based Explainability Methods [Details]
  • ESANN 2025 - Implicit Neural Decision Trees [Details]
D. Guidotti
  • ESANN 2001 - Applications of neuro-fuzzy classification, evaluation and forecasting techniques in agriculture [Details]
Leonardo Guiducci
  • ESANN 2025 - Introducing Intrinsic Motivation in Elastic Decision Transformers [Details]
Fabian Guignard
  • ESANN 2020 - Model Variance for Extreme Learning Machine [Details]
  • ESANN 2020 - On Feature Selection Using Anisotropic General Regression Neural Network [Details]
Vincent Guigue
  • ESANN 2005 - Translation invariant classification of non-stationary signals [Details]
  • ESANN 2015 - Designing semantic feature spaces for brain-reading [Details]
  • ESANN 2017 - Anomaly detection and characterization in smart card logs using NMF and Tweets [Details]
  • ESANN 2018 - Regularize and explicit collaborative filtering with textual attention [Details]
Vincent Guigue
  • ESANN 2020 - Resume: A Robust Framework for Professional Profile Learning & Evaluation [Details]
  • ESANN 2020 - Time Series Prediction using Disentangled Latent Factors [Details]
B. Guijarro-Berdiñas
  • ESANN 2003 - Self-organizing maps and functional networks for local dynamic modeling [Details]
Bertha Guijarro-Berdiñas
  • ESANN 2021 - Federated Learning approach for SpectralClustering [Details]
  • ESANN 2024 - AI-based algorithm for intrusion detection on a real dataset [Details]
Bertha Guijarro-Berdiñas
  • ESANN 2008 - A Regularized Learning Method for Neural Networks Based on Sensitivity Analysis [Details]
  • ESANN 2011 - A distributed learning algorithm based on two-layer artificial neural networks and genetic algorithms [Details]
  • ESANN 2016 - A fast learning algorithm for high dimensional problems: an application to microarrays [Details]
  • ESANN 2016 - Distributed learning algorithm for feedforward neural networks [Details]
  • ESANN 2018 - LANN-DSVD: A privacy-preserving distributed algorithm for machine learning [Details]
Hervé Guillaume
  • ESANN 2005 - Contextual priming for artificial visual perception [Details]
  • ESANN 2011 - Visual place recognition using Bayesian filtering with Markov chains [Details]
Alberto Guillen
  • ESANN 2009 - Applying Mutual Information for Prototype or Instance Selection in Regression Problems [Details]
Josep Guimerá-Tomás
  • ESANN 2012 - Regularized Committee of Extreme Learning Machine for Regression Problems [Details]
S.R. Gunn
  • ESANN 2001 - Texture analysis with the Volterra model using conjugate gradient optimisation [Details]
Siwen Guo
  • ESANN 2019 - Topic-based historical information selection for personalized sentiment analysis [Details]
Li Guo
  • ESANN 2013 - Analysis of Synaptic Weight Distribution in an Izhikevich Network [Details]
Manshan Guo
  • ESANN 2025 - Predictive Coding Dynamics Enhance Model-Brain Similarity [Details]
Yi Guo
  • ESANN 2017 - A performance acceleration algorithm of spectral unmixing via subset selection [Details]
Prashant Gupta
  • ESANN 2021 - Enhash: A Fast Streaming Algorithm For Concept Drift Detection [Details]
Garima Gupta
  • ESANN 2020 - MultiMBNN: Matched and Balanced Causal Inference with Neural Networks [Details]
Andrea Gurioli
  • ESANN 2025 - Trajectory-Embedded Matryoshka Representation Learning for Enhanced Similarity Analysis [Details]
Vaibhav Gusain
  • ESANN 2025 - Improving Privacy Benefits of Redaction [Details]
Thomas Guthier
  • ESANN 2012 - Unsupervised learning of motion patterns [Details]
  • ESANN 2013 - Learning associative spatiotemporal features with non-negative sparse coding [Details]
  • ESANN 2014 - Beyond histograms: why learned structure-preserving descriptors outperform HOG [Details]
José Manuel Gutiérrez
  • ESANN 2012 - Simple reservoirs with chain topology based on a single time-delay nonlinear node [Details]
Pedro A. Gutiérrez
  • ESANN 2013 - Multi-scale Support Vector Machine Optimization by Kernel Target-Alignment [Details]
  • ESANN 2013 - Synthetic over-sampling in the empirical feature space [Details]
Pedro Antonio Gutiérrez
  • ESANN 2014 - Support Vector Ordinal Regression using Privileged Information [Details]
S. Gutjahr
  • ESANN 1997 - Extended Bayesian learning [Details]
Michael Gutmann
  • ESANN 2009 - Learning reconstruction and prediction of natural stimuli by a population of spiking neurons [Details]
Tomasz Gutowski
  • ESANN 2022 - Deep learning for Parkinson’s disease symptom detection and severity evaluation using accelerometer signal [Details]
Tomasz Gutowski
  • No papers found