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
M. Vannucci
  • ESANN 2003 - Comparison of traditional and neural systems for train speed estimation [Details]
Marco Vannucci
  • ESANN 2004 - comparison of different classification methods on castabilty data coming from steelmaking practice [Details]
Lorenzo Vannucci
  • ESANN 2018 - Spatial pooling as feature selection method for object recognition [Details]
Marco Vannucci
  • ESANN 2004 - meaningful discretization of continuous features for association rules mining by means of a SOM [Details]
Tanguy Vansnick
  • ESANN 2025 - SecureBFL: a Blockchain-enhanced federated learning architecture with MPC [Details]
Bruce Vanstone
  • ESANN 2010 - Financial time series forecasting with machine learning techniques: a survey [Details]
Denis Vanvyve
  • ESANN 2005 - clustering using a random walk based distance measure [Details]
Valerie Vaquet
  • ESANN 2021 - Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data [Details]
  • ESANN 2022 - Contrasting Explanation of Concept Drift [Details]
  • ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
  • ESANN 2022 - From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer [Details]
  • ESANN 2023 - Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts [Details]
  • ESANN 2024 - Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty [Details]
  • ESANN 2024 - On the Fine Structure of Drifting Features [Details]
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
  • ESANN 2025 - Adversarial Attacks for Drift Detection [Details]
  • ESANN 2025 - Compression-based $k$NN for Class Incremental Continual Learning [Details]
  • ESANN 2025 - Conceptualizing Concept Drift [Details]
Jonas Vaquet
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
  • ESANN 2025 - Compression-based $k$NN for Class Incremental Continual Learning [Details]
A. Varfis
  • ESANN 1993 - An intuitive characterization for the reference vectors of a Kohonen map [Details]
  • ESANN 1994 - Decoding functions for Kohonen maps [Details]
  • ESANN 1996 - Error rate estimation via cross-validation and learning curve theory [Details]
Georgios Varisteas
  • ESANN 2019 - time series modelling of market price in real-time bidding [Details]
M. Varsta
  • ESANN 1998 - Recurrent SOM with local linear models in time series prediction [Details]
  • ESANN 2000 - Analytical comparison of the Temporal Kohonen Map and the Recurrent Self Organizing Map [Details]
Simon Vary
  • ESANN 2023 - An Alternating Minimization Algorithm with Trajectory for Direct Exoplanet Detection [Details]
Daniel Vašata
  • ESANN 2020 - Unsupervised Latent Space Translation Network [Details]
Cristina Vasconcelos
  • ESANN 2015 - Revisiting ant colony algorithms to seismic faults detection [Details]
Stefano Vassanelli
  • ESANN 2023 - Real-time Detection of Evoked Potentials by Deep Learning: a Case Study [Details]
S. Vassiliadis
  • ESANN 1995 - XOR and backpropagation learning: in and out of the chaos? [Details]
G. Vaucher
  • ESANN 1997 - An algebra for recognition of spatio-temporal forms [Details]
  • ESANN 2003 - A Spiking Machine for Human-Computer Interactions (Design methodology) [Details]
M.L. Vaughn
  • ESANN 2002 - A data vizualisation method for investigating the reliability of a high-dimensional low-back-pain MLP network [Details]
Bernard Vayssade
  • No papers found
Gustavo E. Vazquez
  • ESANN 2010 - Adaptive matrix distances aiming at optimum regression subspaces [Details]
F.X. Vazquez
  • ESANN 1995 - A deterministic method for establishing the initial conditions in the RCE algorithm [Details]
David Vázquez-Lema
  • ESANN 2023 - Evaluating Curriculum Learning Strategies for Pancreatic Cancer Prediction [Details]
Seyed Shakib Vedaie
  • ESANN 2020 - Machine learning framework for control in classical and quantum domains [Details]
Saradhi Vedula
  • ESANN 2007 - Kernel-based online machine learning and support vector reduction [Details]
Roland Veen
  • ESANN 2024 - Interpreting Hybrid AI through Autodecoded Latent Space Entities [Details]
Lokesh Veeramacheneni
  • ESANN 2024 - On the Stability of Neural Segmentation in Radiology [Details]
David Veganzones
  • ESANN 2014 - Finding Originally Mislabels with MD-ELM [Details]
Haroldo Velho
  • ESANN 2019 - Weightless neural systems for deforestation surveillance and image-based navigation of UAVs in the Amazon forest [Details]
Petar Velickovic
  • ESANN 2018 - Multi-omics data integration using cross-modal neural networks [Details]