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
Andreas Mazur
  • No papers found
Andreas Mazur
  • ESANN 2022 - Improving Zorro Explanations for Sparse Observations with Dense Proxy Data [Details]
  • ESANN 2024 - Visualizing and Improving 3D Mesh Segmentation with DeepView [Details]
Vittorio Mazzia
  • No papers found
Mauro Mazzieri
  • ESANN 2010 - Modeling contextualized textual knowledge as a Long-Term Working Memory [Details]
Giuseppe Mazzitelli
  • ESANN 2008 - An automatic identifier of Confinement Regimes at JET combining Fuzzy Logic and Classification Trees [Details]
George McConnon
  • ESANN 2010 - A novel interactive biometric passport photograph alignment system [Details]
Ryan McConville
  • ESANN 2018 - Person Identification and Discovery With Wrist Worn Accelerometer Data [Details]
C. McCormack
  • ESANN 1996 - Using a Meta Neural Network for RPROP parameter adaptation [Details]
Klaus McDonald-Maier
  • ESANN 2009 - FPGA-based enhanced probabilistic convergent weightless Network for human Iris recognition [Details]
  • ESANN 2010 - Model Learning from Weights by Adaptive Enhanced Probabilistic Convergent Network [Details]
Ben McElroy
  • ESANN 2012 - Highly efficient localisation utilising weightless neural systems [Details]
S. McGlinchey
  • ESANN 1998 - Invariant feature maps for analysis of orientations in image data [Details]
  • ESANN 1999 - Comparison of Kohonen, scale-invariant and GTM self-organising maps for interpretation of spectral data [Details]
J. McNames
  • ESANN 2000 - Local model optimization for time series prediction [Details]
Duccio Meconcelli
  • No papers found
Duccio Meconcelli
  • ESANN 2022 - Deep Learning Approaches for mice glomeruli segmentation [Details]
Francesca Medda
  • ESANN 2021 - A Baseline for Shapley Values in MLPs: from Missingness to Neutrality [Details]
Aref Meddeb
  • No papers found
Talles Medeiros
  • ESANN 2007 - A new decision strategy in multi-objective training of the artificial neural networks [Details]
  • ESANN 2007 - Prediction of post-synaptic activity in proteins using recursive feature elimination [Details]
Fábio Medeiros Rangel
  • ESANN 2019 - Memory Efficient Weightless Neural Network using Bloom Filter [Details]
Wannes Meert
  • ESANN 2014 - Context- and cost-aware feature selection in ultra-low-power sensor interfaces [Details]
  • ESANN 2018 - Feature noise tuning for resource efficient Bayesian Network Classifiers [Details]
Jérôme Meessen
  • ESANN 2009 - Embedding Proximal Support Vectors into Randomized Trees [Details]
Stijn Meganck
  • ESANN 2011 - Inferring the causal decomposition under the presence of deterministic relations [Details]
István Megyeri
  • ESANN 2020 - Attacking Model Sets with Adversarial Examples [Details]
  • ESANN 2022 - PCA improves the adversarial robustness of neural networks [Details]
  • ESANN 2024 - Adversarial Training without Hard Labels [Details]
Istvan Megyeri
  • ESANN 2019 - Adversarial robustness of linear models: regularization and dimensionality [Details]
Siamak Mehrkanoon
  • ESANN 2011 - Symbolic computing of LS-SVM based models [Details]
  • ESANN 2017 - Scalable Hybrid Deep Neural Kernel Networks [Details]
  • ESANN 2018 - Shallow and Deep Models for Domain Adaptation problems [Details]
Siamak Mehrkanoon
  • ESANN 2020 - Learning from partially labeled data [Details]
  • ESANN 2020 - Modelling human sound localization with deep neural networks. [Details]
  • ESANN 2021 - Deep Graph Convolutional Networks for Wind Speed Prediction [Details]
  • ESANN 2021 - Enhancing brain decoding using attention augmented deep neural networks [Details]
Siamak Mehrkanoon
  • ESANN 2024 - Dual Stream Graph Transformer Fusion Networks for Enhanced Brain Decoding [Details]
Farrokh Mehryary
  • ESANN 2020 - Entity-Pair Embeddings for Improving Relation Extraction in the Biomedical Domain [Details]
Martin Meier
  • ESANN 2013 - Perceptual grouping through competition in coupled oscillator networks [Details]
René Meier
  • ESANN 2009 - The Use of ANN for Turbo Engine Applications [Details]
Peter Meier
  • ESANN 2020 - Domain Invariant Representations with Deep Spectral Alignment [Details]