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
Gabriel Guarisa
  • ESANN 2019 - Prediction of palm oil production with an enhanced n-Tuple Regression Network [Details]
Gabriel Guarisa
  • ESANN 2020 - Interpretation of Model Agnostic Classifiers via Local Mental Images [Details]
Jayavardhana Gubbi
  • No papers found
Jayavardhana Gubbi
  • ESANN 2022 - Appearance-Context aware Axial Attention for Fashion Landmark Detection [Details]
Anne Guerin-Dugue
  • ESANN 2013 - A new metric for dissimilarity data classification based on Support Vector Machines optimization [Details]
A. Guérin-Dugué
  • ESANN 1996 - Interpreting data through neural and statistical tools [Details]
  • ESANN 1997 - Scene categorisation by curvilinear component analysis of low frequency spectra [Details]
  • ESANN 2002 - Searching for the embedded manifolds in high-dimensional data, problems and unsolved questions [Details]
Yann Guermeur
  • ESANN 2018 - A sharper bound on the Rademacher complexity of margin multi-category classifiers [Details]
Fabio Guerra
  • No papers found
Michele Guerra
  • ESANN 2023 - Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability [Details]
E. Guerrero
  • ESANN 2000 - A statistical model selection strategy applied to neural networks [Details]
E. Guerrero Vazquez
  • ESANN 2002 - A resampling and multiple testing-based procedure for determining the size of a neural network [Details]
  • ESANN 2002 - Noise derived information criterion for model selection [Details]
  • ESANN 2003 - A new Meta Machine Learning (MML) method based on combining non-significant different neural networks [Details]
Christoph Guger
  • ESANN 2009 - Brain Computer Interface for Virtual Reality Control [Details]
Rima Guidara
  • ESANN 2007 - Markovian blind separation of non-stationary temporally correlated sources [Details]
D. Guidotti
  • ESANN 2001 - Applications of neuro-fuzzy classification, evaluation and forecasting techniques in agriculture [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]
Leonardo Guiducci
  • ESANN 2025 - Introducing Intrinsic Motivation in Elastic Decision Transformers [Details]
  • ESANN 2026 - Unpacking the Role of Intrinsic Motivation in Elastic Decision Transformers: A Post-Hoc Analysis of Embedding Geometry and Performance [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 2020 - Resume: A Robust Framework for Professional Profile Learning & Evaluation [Details]
  • ESANN 2020 - Time Series Prediction using Disentangled Latent Factors [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]
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]
  • ESANN 2026 - FedHENet: A Frugal Federated Learning Framework for Heterogeneous Environments [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]
Yi Guo
  • ESANN 2017 - A performance acceleration algorithm of spectral unmixing via subset selection [Details]
Manshan Guo
  • ESANN 2025 - Predictive Coding Dynamics Enhance Model-Brain Similarity [Details]
  • ESANN 2026 - Predictive Coding inspired convolutional networks can capture the neural dynamics of recurrent processing in human image recognition [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]