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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
thomas ashby
  • ESANN 2018 - Cache-efficient Gradient Descent Algorithm [Details]
Praveen Cheriyan Ashok
  • ESANN 2012 - Classifying Scotch Whisky from near-infrared Raman spectra with a Radial Basis Function Network with Relevance Learning [Details]
Akash Ashokan
  • ESANN 2023 - Segmentation and Analysis of Lumbar Spine MRI Scans for Vertebral Body Measurements [Details]
Pooya Ashtari
  • No papers found
Pooya Ashtari
  • ESANN 2022 - A Kernel Based Multilinear SVD Approach for Multiple Sclerosis Profiles Classification [Details]
Tewari Ashutosh
  • No papers found
J.-P. Asselin de Beauville
  • ESANN 1998 - NAR time-series prediction: a Bayesian framework and an experiment [Details]
  • ESANN 2000 - An algorithm for the addition of time-delayed connections to recurrent neural networks [Details]
Zhenisbek Assylbekov
  • ESANN 2021 - Geometric Probing of Word Vectors [Details]
Stylianos Asteriadis
  • ESANN 2019 - Bridging face and sound modalities through domain adaptation metric learning [Details]
Nicolas Astorga
  • ESANN 2018 - Latent representations of transient candidates from an astronomical image difference pipeline using Variational Autoencoders [Details]
Franc Švegl
  • No papers found
Witali Aswolinskiy
  • ESANN 2016 - Modelling of parameterized processes via regression in the model space [Details]
M. A. Atencia
  • ESANN 2001 - Numerical implementation of continuous Hopfield networks for optimization [Details]
Miguel Atencia
  • ESANN 2005 - Stochastic analysis of the Abe formulation of Hopfield networks [Details]
  • ESANN 2005 - Two or three things that we (intend to) know about Hopfield and Tank networks [Details]
  • ESANN 2011 - Statistical properties of the `Hopfield estimator' of dynamical systems [Details]
  • ESANN 2018 - Non-negative Matrix Factorization for Medical Imaging [Details]
Dimitrios Athanasakis
  • ESANN 2018 - Sleep staging with deep learning: a convolutional model [Details]
Christos Athanasiadis
  • ESANN 2019 - Bridging face and sound modalities through domain adaptation metric learning [Details]
Jamal Atif
  • ESANN 2020 - Estimating Individual Treatment Effects through Causal Populations Identification [Details]
Ferhat ATTAL
  • ESANN 2015 - Powered-Two-Wheeler safety critical events recognition using a mixture model with quadratic logistic functions [Details]
  • ESANN 2018 - CDTW-based classification for Parkinson's Disease diagnosis [Details]
Ferhat Attal
  • ESANN 2024 - Multidimensional CDTW-based features for Parkinson's Disease classification [Details]
  • ESANN 2025 - Semantic Segmentation for Waterbody Extraction Using Superpixels and Convolutional Neural Networks Classifier [Details]
J.-G. Attali
  • ESANN 1995 - Functional approximation by perceptrons: a new approach [Details]
Conrad Attard
  • ESANN 2008 - The impact of axon wiring costs on small neuronal networks [Details]
Ulrike I. Attenberger
  • No papers found
Ulrike I. Attenberger
  • ESANN 2022 - Improving Intensive Care Chest X-Ray Classification by Transfer Learning and Automatic Label Generation [Details]
  • ESANN 2024 - On the Stability of Neural Segmentation in Radiology [Details]
Virginie Attina
  • ESANN 2009 - Sensors selection for P300 speller brain computer interface [Details]
Romis Attux
  • ESANN 2013 - Error entropy criterion in echo state network training [Details]
  • ESANN 2014 - Analysis of the Weighted Fuzzy C-means in the problem of source location [Details]
  • ESANN 2016 - An Immune-Inspired, Dependence-Based Approach to Blind Inversion of Wiener Systems [Details]
L. Aubry
  • ESANN 2001 - More on stationnary points in Independent Component Analysis [Details]
Julien Audiffren
  • ESANN 2015 - Online Learning with Operator-valued Kernels [Details]
D. Auer
  • ESANN 2003 - Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis [Details]
Dante Augusto Couto Barone
  • ESANN 2019 - Using Deep Learning and Evolutionary Algorithms for Time Series Forecasting [Details]
Sompun Aumpawan
  • ESANN 2011 - Stability of Neural Network Control for Uncertain Sampled-Data Systems [Details]

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