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 Herzog
  • ESANN 2004 - Learning by geometrical shape changes of dendritic spines [Details]
Tom Heskes
  • ESANN 2004 - Novel approximations for inference and learning in nonlinear dynamical systems [Details]
  • ESANN 2009 - Exploring the impact of alternative feature representations on BCI classification [Details]
  • ESANN 2009 - Multi-task Preference learning with Gaussian Processes [Details]
  • ESANN 2011 - A structure independent algorithm for causal discovery [Details]
  • ESANN 2011 - Learning of causal relations [Details]
T. Heskes
  • ESANN 1994 - Stochastics of on-line back-propagation [Details]
  • ESANN 1999 - Model clustering by deterministic annealing [Details]
Z. Heszberger
  • ESANN 2000 - An optimization neural network model with time-dependent and lossy dynamics [Details]
Manuel Hettich
  • ESANN 2024 - Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange [Details]
Moritz Heusinger
  • ESANN 2020 - Random Projection in supervised non-stationary environments [Details]
  • ESANN 2021 - Federated Learning - Methods, Applications and beyond [Details]
Moritz Heusinger
  • ESANN 2019 - Reactive Soft Prototype Computing for frequent reoccurring Concept Drift [Details]
M. Lautaro Hickmann
  • ESANN 2023 - Potential analysis of a Quantum RL controller in the context of autonomous driving [Details]
  • ESANN 2025 - Enhancing Machine Learning with Quantum Methods [Details]
Djoerd Hiemstra
  • ESANN 2014 - Comparison of local and global undirected graphical models [Details]
G.D. Hilakos
  • ESANN 1995 - Alternative output representation schemes affect learning and generalization of back-propagation ANNs; a decision support application [Details]
M. Hilario
  • ESANN 1995 - Neurosymbolic integration: unified versus hybrid approaches [Details]
Uwe Himmelreich
  • ESANN 2016 - Initializing nonnegative matrix factorization using the successive projection algorithm for multi-parametric medical image segmentation [Details]
  • ESANN 2017 - Comparison of manual and semi-manual delineations for classifying glioblastoma multiforme patients based on histogram and texture MRI features [Details]
Xavier Hinaut
  • ESANN 2016 - Activity recognition with echo state networks using 3D body joints and objects category [Details]
  • ESANN 2016 - Semantic Role Labelling for Robot Instructions using Echo State Networks [Details]
Christopher J. Hinde
  • No papers found
Fabian Hinder
  • ESANN 2025 - Compression-based $k$NN for Class Incremental Continual Learning [Details]
  • ESANN 2025 - Conceptualizing Concept Drift [Details]
Fabian Hinder
  • ESANN 2021 - Concept Drift Segmentation via Kolmogorov-Trees [Details]
  • ESANN 2022 - Contrasting Explanation of Concept Drift [Details]
  • ESANN 2022 - Federated learning vector quantization for dealing with drift between nodes [Details]
  • ESANN 2023 - Feature Selection for Concept Drift Detection [Details]
  • ESANN 2025 - Adversarial Attacks for Drift Detection [Details]
Fabian Hinder
  • ESANN 2024 - Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty [Details]
  • ESANN 2024 - On the Fine Structure of Drifting Features [Details]
  • ESANN 2024 - Self-Supervised Learning from Incrementally Drifting Data Streams [Details]
Georg Hinselmann
  • ESANN 2011 - Fast Data Mining with Sparse Chemical Graph Fingerprints by Estimating the Probability of Unique Patterns [Details]
Geoffrey Hinton
  • ESANN 2008 - Improving a statistical language model by modulating the effects of context words [Details]
  • ESANN 2009 - Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine [Details]
  • ESANN 2011 - Using very deep autoencoders for content-based image retrieval [Details]
Tobias Hinz
  • ESANN 2018 - Inferencing based on unsupervised learning of disentangled representations [Details]
Marcelo Hirakuri
  • ESANN 2005 - Using CMU PIE Human Face Database to a Convolutional Neural Network - Neocognitron [Details]
K. Hirasawa
  • ESANN 2003 - Online Identification and Control of a PV-Supplied DC Motor Using Universal Learning Networks [Details]
Niklas Hjuler
  • ESANN 2019 - Detecting Ghostwriters in High Schools [Details]
K. Hlavackova
  • ESANN 1994 - An optimized RBF network for approximation of functions [Details]
  • ESANN 1994 - Approximation of continuous functions by RBF and KBF networks [Details]
  • ESANN 1995 - An upper estimate of the error of approximation of continuous multivariable functions by KBF networks [Details]
  • ESANN 1996 - Rates of approximation of real-valued boolean functions by neural networks [Details]
Katerina Hlavackova-Schindler
  • ESANN 2007 - Computational Intelligence approaches to causality detection [Details]
S.L. Ho
  • ESANN 2004 - Time Series Analysis for Quality Improvement: a Soft Computing Approach [Details]
Marius Hobbhahn
  • ESANN 2020 - Sequence Classification using Ensembles of Recurrent Generative Expert Modules [Details]
Sebastian Hoch
  • ESANN 2021 - Sample efficient localization and stage prediction with autoencoders [Details]
V. J. Hodge
  • ESANN 2001 - An integrated neural IR system [Details]
L. Hoegaerts
  • ESANN 2003 - Kernel PLS variants for regression [Details]