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
Nicola De Quattro
  • ESANN 2023 - Simultaneous failures classification in a predictive maintenance case [Details]
Sven De Rijcke
  • ESANN 2020 - ASAP - A Sub-sampling Approach for Preserving Topological Structures [Details]
Kylliann De Santiago
  • ESANN 2023 - Mixture of stochastic block models for multiview clustering [Details]
Tom De Schepper
  • ESANN 2025 - Reducing the stability gap for continual learning at the edge with class balancing [Details]
S. de Schonen
  • ESANN 1999 - Modeling face recognition learning in early infant development [Details]
Cédric De Schryver
  • ESANN 2022 - Machine learning for automated quality control in injection moulding manufacturing [Details]
Cédric De Schryver
  • No papers found
Thibault de Surrel
  • ESANN 2026 - SPDNet-AE: a Compact SPD Representation through Riemannian Autoencoding [Details]
Marina De Tommaso
  • No papers found
Emmanuel DE VERDALLE
  • ESANN 2012 - A CUSUM approach for online change-point detection on curve sequences [Details]
Christophe De Vleeschouwer
  • ESANN 2023 - Don't skip the skips: autoencoder skip connections improve latent representation discrepancy for anomaly detection [Details]
  • ESANN 2024 - Graph-cut-assisted CNN training for pulmonary embolism segmentation [Details]
  • ESANN 2026 - Towards Understanding The Winner-Take-Most Behavior Of Neural Network Representations [Details]
Christophe De Vleeschouwer
  • ESANN 2009 - Embedding Proximal Support Vectors into Randomized Trees [Details]
  • ESANN 2019 - Experimental study of the neuron-level mechanisms emerging from backpropagation [Details]
Gert-Jan de Vries
  • ESANN 2017 - Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders [Details]
Bert de Vries
  • ESANN 2009 - Bayesian periodogram smoothing for speech enhancement [Details]
Harm de Vries
  • ESANN 2016 - Deep Learning Vector Quantization [Details]
T. de Vries
  • ESANN 1998 - Parsimonious learning feed-forward control [Details]
Maarten De Waard
  • ESANN 2015 - Pareto Local Search for MOMDP Planning [Details]
Diogo de-Freitas
  • ESANN 2018 - Evolutionary Composition of Customized Fault Localization Heuristics [Details]
Klaus Debes
  • ESANN 2009 - Forward feature selection using Residual Mutual Information [Details]
Christine Decaestecker
  • ESANN 2025 - Ranking the scores of algorithms with confidence [Details]
Jérémie Decock
  • ESANN 2014 - Direct Model-Predictive Control [Details]
Jonas Degrave
  • ESANN 2016 - Spatial Chirp-Z Transformer Networks [Details]
J. Dehaene
  • ESANN 1993 - Locally implementable learning with isospectral matrix flows [Details]
  • ESANN 1995 - Adaptive signal processing with unidirectional Hebbian adaptation laws [Details]
Frédéric Dehais
  • ESANN 2024 - Deep Riemannian Neural Architectures for Domain Adaptation in Burst cVEP-based Brain Computer Interface [Details]
Mathieu Dehouck
  • ESANN 2019 - Modal sense classification with task-specific context embeddings [Details]
Marc Deisenroth
  • ESANN 2008 - Model-Based Reinforcement Learning with Continuous States and Actions [Details]
A. Deiss
  • ESANN 1998 - Selecting among candidate basis functions by crosscorrelations [Details]
Hanne Dejonghe
  • ESANN 2026 - THDC: Training Hyperdimensional Computing Models with Backpropagation [Details]
Oleksiy Dekhtyarenko
  • ESANN 2005 - Averaging on Riemannian manifolds and unsupervised learning using neural associative memory [Details]
  • ESANN 2005 - Phase transition in sparse associative neural networks [Details]
Alberto Antonio Del Barrio García
  • ESANN 2019 - Design of Power-Efficient FPGA Convolutional Cores with Approximate Log Multiplier [Details]