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
Aman Arora
  • No papers found
Aman Arora
  • ESANN 2022 - Pruning Weightless Neural Networks [Details]
A. Arquero
  • ESANN 1999 - Supervised Art-II: a new neural network architecture, with quicker learning algorithm, for learning and classifying multivaled input patterns [Details]
Joel Arrais
  • ESANN 2021 - Decay Momentum for Improving Federated Learning [Details]
  • ESANN 2021 - Improvement on Generative Adversarial Network for Targeted Drug Design [Details]
  • ESANN 2021 - Multiobjective Reinforcement Learning in Optimized Drug Design [Details]
  • ESANN 2023 - Convolutional Transformer via Graph Embeddings for Few-shot Toxicity and Side Effect Prediction [Details]
Octavio Arriaga
  • ESANN 2019 - Real-time Convolutional Neural Networks for emotion and gender classification [Details]
Valentina Arrigoni
  • ESANN 2017 - Approximate operations in Convolutional Neural Networks with RNS data representation [Details]
André Artelt
  • ESANN 2020 - Efficient computation of counterfactual explanations of LVQ models [Details]
  • ESANN 2022 - Contrasting Explanation of Concept Drift [Details]
  • ESANN 2022 - Improving Zorro Explanations for Sparse Observations with Dense Proxy Data [Details]
  • ESANN 2022 - Model Agnostic Local Explanations of Reject [Details]
thierry Artieres
  • ESANN 2011 - Hybrid HMM and HCRF model for sequence classification [Details]
  • ESANN 2015 - Designing semantic feature spaces for brain-reading [Details]
  • ESANN 2018 - transferring style in motion capture sequences with adversarial learning [Details]
Kai Arulkumaran
  • ESANN 2020 - Incorporating Human Priors into Deep Reinforcement Learning for Robotic Control [Details]
Carles Arús
  • ESANN 2010 - Spectral Prototype Extraction for dimensionality reduction in brain tumour diagnosis [Details]
  • ESANN 2016 - A machine learning pipeline for supporting differentiation of glioblastomas from single brain metastases [Details]
C. Arus
  • ESANN 2002 - The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signals [Details]
R. Arutyunyan
  • ESANN 2000 - Application of MLP and stochastic simulations for electricity load forecasting in Russia [Details]
Miika Arvonen
  • ESANN 2020 - Respiratory Pattern Recognition from Low-Resolution Thermal Imaging [Details]
Minoru Asada
  • ESANN 2009 - Studies on reservoir initialization and dynamics shaping in echo state networks [Details]
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]