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
Michael Gebauer
  • ESANN 2021 - Toxicity Detection in Online Comments with Limited Data: A Comparative Analysis [Details]
Dries Geebelen
  • ESANN 2012 - Joint Regression and Linear Combination of Time Series for Optimal Prediction [Details]
Xavier Geets
  • ESANN 2019 - Application of deep neural networks for automatic planning in radiation oncology treatments [Details]
Peter Geibel
  • ESANN 2004 - SVM learning with the SH inner product [Details]
Fabian Geiger
  • ESANN 2025 - Resource-Aware Cooperation in Federated Learning [Details]
Katja Geirhos
  • ESANN 2020 - Approximating Archetypal Analysis Using Quantum Annealing [Details]
Matthieu Geist
  • ESANN 2009 - Kernelizing Vector Quantization Algorithms [Details]
Sylvain Gelly
  • ESANN 2006 - Learning for stochastic dynamic programming [Details]
Alain Gély
  • ESANN 2018 - K-spectral centroid: extension and optimizations [Details]
Yanyan Geng
  • ESANN 2017 - Learning convolutional neural network to maximize Pos@Top performance measure [Details]
Dominique Genoud
  • ESANN 2021 - Improved and Generalized Vine Line Detection on Aerial Images Using Asymmetrical Neural Networks and ML Subclassifiers [Details]
Bogdan Georgiev
  • ESANN 2020 - Explorations in Quantum Neural Networks with Intermediate Measurements [Details]
  • ESANN 2020 - On Learning a Control System without Continuous Feedback [Details]
Pando Georgiev
  • ESANN 2004 - Robust overcomplete matrix recovery for sparse sources using a generalized Hough transform [Details]
Alexander Gepperth
  • ESANN 2020 - A Survey of Machine Learning applied to Computer Networks [Details]
  • ESANN 2022 - An empirical comparison of generators in replay-based continual learning [Details]
  • ESANN 2022 - Tutorial - Continual Learning beyond classification [Details]
  • ESANN 2024 - Continual Learning of Deep Neural Networks in The Age of Big Data [Details]
  • ESANN 2025 - Don't drift away: Advances and Applications of Streaming and Continual Learning [Details]
Alex Gepperth
  • ESANN 2025 - Continual Unlearning through Memory Suppression [Details]
  • ESANN 2025 - Reward Incremental Learning [Details]
Alexander Gepperth
  • ESANN 2005 - Applications of multi-objective structure optimization [Details]
  • ESANN 2006 - Visual object classification by sparse convolutional neural networks [Details]
  • ESANN 2008 - Computationally Efficient Neural Field Dynamics [Details]
  • ESANN 2014 - Discrimination of visual pedestrians data by combining projection and prediction learning [Details]
  • ESANN 2014 - Neural network based 2D/3D fusion for robotic object recognition [Details]
  • ESANN 2015 - A simple technique for improving multi-class classification with neural networks [Details]
  • ESANN 2015 - Resource-efficient Incremental learning in very high dimensions [Details]
  • ESANN 2015 - Using self-organizing maps for regression: the importance of the output function [Details]
  • ESANN 2016 - Incremental learning algorithms and applications [Details]
  • ESANN 2016 - Towards incremental deep learning: multi-level change detection in a hierarchical visual recognition architecture [Details]
  • ESANN 2017 - Acceleration of Prototype Based Models with Cascade Computation [Details]
  • ESANN 2018 - Incremental learning with deep neural networks using a test-time oracle [Details]
Dario Gerace
  • ESANN 2020 - An quantum algorithm for feedforward neural networks tested on existing quantum hardware [Details]
Steve Gerges
  • ESANN 2013 - Learning associative spatiotemporal features with non-negative sparse coding [Details]
Felipe Gerhard
  • ESANN 2009 - A robust biologically plausible implementation of ICA-like learning [Details]
Peter Gerjets
  • ESANN 2011 - Classifying mental states with machine learning algorithms using alpha activity decline [Details]
Cecile Germain
  • ESANN 2016 - How machine learning won the Higgs boson challenge [Details]
  • ESANN 2018 - Systematics aware learning : a case study in high energy physics [Details]
F.A. Gers K. Gersmann
  • ESANN 2003 - Improving iterative repair strategies for scheduling with the SVM [Details]
Andreas O. H. Gerstner
  • No papers found
Andreas O. H. Gerstner
  • ESANN 2022 - Hyperspectral Wavelength Analysis with U-Net for Larynx Cancer Detection [Details]
Pierre Geurts
  • ESANN 2024 - Trust in Artificial Intelligence: Beyond Interpretability [Details]
Pierre Geurts
  • ESANN 2006 - Elucidating the structure of genetic regulatory networks: a study of a second order dynamical model on artificial data [Details]
  • ESANN 2012 - L1-based compression of random forest models [Details]
  • ESANN 2014 - Data normalization and supervised learning to assess the condition of patients with multiple sclerosis based on gait analysis [Details]
Tina Geweniger
  • ESANN 2025 - Integrating Class Relation Knowledge in Probabilistic Learning Vector Quantization [Details]
Tina Geweniger
  • ESANN 2008 - Magnification Control in Relational Neural Gas [Details]
  • ESANN 2009 - Fuzzy Fleiss-kappa for Comparison of Fuzzy Classifiers [Details]
  • ESANN 2009 - Median Variant of Fuzzy c-Means [Details]
  • ESANN 2010 - Extending FSNPC to handle data points with fuzzy class assignments [Details]
  • ESANN 2010 - Learning vector quantization for heterogeneous structured data [Details]
  • ESANN 2011 - Multivariate class labeling in Robust Soft LVQ [Details]
  • ESANN 2011 - Optimization of Parametrized Divergences in Fuzzy c-Means [Details]
  • ESANN 2012 - Modified Conn-Index for the evaluation of fuzzy clusterings [Details]
  • ESANN 2013 - Border sensitive fuzzy vector quantization in semi-supervised learning [Details]
R. Ghaderi
  • ESANN 1999 - AdaBoost and neural networks [Details]