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
Sofia De La Riva
  • ESANN 2016 - Assessment of diabetic retinopathy risk with random forests [Details]
Gaël de Lannoy
  • ESANN 2009 - Improving the transition modelling in hidden Markov models for ECG segmentation [Details]
  • ESANN 2011 - Class-Specific Feature Selection for One-Against-All Multiclass SVMs [Details]
  • ESANN 2019 - Machine learning in research and development of new vaccines products: opportunities and challenges [Details]
Gael de Lannoy
  • ESANN 2020 - An agile machine learning project in pharma - developing a Mask R-CNN-based web application for bacterial colony counting [Details]
  • ESANN 2020 - Deep Learning to Detect Bacterial Colonies for the Production of Vaccines [Details]
  • ESANN 2020 - Machine learning in the biopharma industry [Details]
Lieven De Lathauwer
  • ESANN 2018 - A variable projection method for block term decomposition of higher-order tensors [Details]
Ana de Lima
  • ESANN 2004 - Modelling of biologically plausible excitatory networks: emergence and modulation of neural synchrony [Details]
  • ESANN 2005 - Spike-timing-dependent plasticity in 'small world' networks [Details]
Ana D. de Lima
  • ESANN 2008 - Simulation of a recurrent neurointerface with sparse electrical connections [Details]
Anna D. de Lima
  • ESANN 2006 - Connection strategies in neocortical networks [Details]
Hannes De Meulemeester
  • No papers found
Hannes De Meulemeester
  • ESANN 2022 - Recurrent Restricted Kernel Machines for Time-series Forecasting [Details]
Bart De Moor
  • ESANN 2022 - Recurrent Restricted Kernel Machines for Time-series Forecasting [Details]
Bart De Moor
  • No papers found
Bart De Moor
  • ESANN 2004 - sparse LS-SVMs using additive regularization with a penalized validation criterion [Details]
  • ESANN 2012 - Deconvolution in nonparametric statistics [Details]
  • ESANN 2012 - Joint Regression and Linear Combination of Time Series for Optimal Prediction [Details]
  • ESANN 2012 - Weighted/Structured Total Least Squares problems and polynomial system solving [Details]
  • ESANN 2012 - maximum likelihood estimation and polynomial system solving [Details]
B. De Moor
  • ESANN 1995 - NLq theory: unifications in the theory of neural networks, systems and control [Details]
  • ESANN 2001 - Automatic relevance determination for Least Squares Support Vector Machines classifiers [Details]
  • ESANN 2003 - Kernel PLS variants for regression [Details]
Joaquim de Moura
  • ESANN 2019 - Computerized tool for identification and enhanced visualization of Macular Edema regions using OCT scans [Details]
Joaquim de Moura
  • ESANN 2021 - Comprehensive Analysis of the Screening of COVID-19 Approaches in Chest X-ray Images from Portable Devices [Details]
Arnaud de Myttenaere
  • ESANN 2015 - Reducing offline evaluation bias of collaborative filtering [Details]
  • ESANN 2015 - Using the Mean Absolute Percentage Error for Regression Models [Details]
Francisco de Nolasco Santos
  • ESANN 2022 - Anomaly detection and representation learning in an instrumented railway bridge [Details]
  • ESANN 2022 - Minkowski logarithmic error: A physics-informed neural network approach for wind turbine lifetime assessment [Details]
Francisco de Nolasco Santos
  • No papers found
Wilson R. de Oliveira
  • ESANN 2014 - Advances on Weightless Neural Systems [Details]
  • ESANN 2014 - Probabilistic automata simulation with single layer weightless neural networks [Details]
  • ESANN 2014 - Training a classical weightless neural network in a quantum computer [Details]
  • ESANN 2014 - Vector space weightless neural networks [Details]
Wilson de Oliveira
  • ESANN 2009 - Quantum RAM Based Neural Netoworks [Details]
Thiago de Paulo Faleiros
  • ESANN 2016 - On the equivalence between algorithms for Non-negative Matrix Factorization and Latent Dirichlet Allocation [Details]
Aloisio Carlos de Pina
  • ESANN 2006 - Using Regression Error Characteristic Curves for Model Selection in Ensembles of Neural Networks [Details]
Henri De Plaen
  • No papers found
Henri De Plaen
  • ESANN 2022 - Recurrent Restricted Kernel Machines for Time-series Forecasting [Details]
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]