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
Reinhild Schnabel
  • ESANN 2004 - Learning by geometrical shape changes of dendritic spines [Details]
Daniel Schneegaß
  • ESANN 2006 - OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method [Details]
Daniel Schneegass
  • ESANN 2007 - Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification [Details]
  • ESANN 2007 - Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments [Details]
  • ESANN 2007 - The Intrinsic Recurrent Support Vector Machine [Details]
  • ESANN 2008 - Safe exploration for reinforcement learning [Details]
Helen Schneider
  • ESANN 2022 - Improving Intensive Care Chest X-Ray Classification by Transfer Learning and Automatic Label Generation [Details]
  • ESANN 2023 - Segmentation and Analysis of Lumbar Spine MRI Scans for Vertebral Body Measurements [Details]
Axel Schneider
  • ESANN 2024 - Similarity-Based Zero-Shot Domain Adaptation for Wearables [Details]
Petra Schneider
  • ESANN 2007 - Relevance matrices in LVQ [Details]
  • ESANN 2008 - Generalized matrix learning vector quantizer for the analysis of spectral data [Details]
  • ESANN 2009 - Hyperparameter Learning in Robust Soft LVQ [Details]
  • ESANN 2009 - Nonlinear Discriminative Data Visualization [Details]
  • ESANN 2010 - Divergence based Learning Vector Quantization [Details]
  • ESANN 2011 - Multivariate class labeling in Robust Soft LVQ [Details]
  • ESANN 2012 - Matrix relevance LVQ in steroid metabolomics based classification of adrenal tumors [Details]
Helen Schneider
  • No papers found
Andrea Schnepf
  • ESANN 2020 - 3D U-Net for Segmentation of Plant Root MRI Images in Super-Resolution [Details]
Dominik Schnitzer
  • ESANN 2014 - Choosing the Metric in High-Dimensional Spaces Based on Hub Analysis [Details]
François Schnitzler
  • ESANN 2022 - Feature Compression Using Dynamic Switches in Multi-split CNNs [Details]
François Schnitzler
  • ESANN 2010 - Towards sub-quadratic learning of probability density models in the form of mixtures of trees [Details]
  • ESANN 2012 - L1-based compression of random forest models [Details]
François Schnitzler
  • No papers found
Pierre-Yves Schobbens
  • ESANN 2024 - CNNGen: A Generator and a Dataset for Energy-Aware Neural Architecture Search [Details]
G. Schock
  • ESANN 2000 - Nonlinear, statistical data-analysis for the optimal construction of neural-network inputs with the concept of a mutual information [Details]
Patrick Schoefer
  • ESANN 2025 - The Regulatory Character of Boredom in AI - Towards a Self-Regulating System based on Spiking Neural Networks [Details]
Bernhard Schoelkopf
  • ESANN 2008 - Learning Inverse Dynamics: a Comparison [Details]
Greg Schoenau
  • ESANN 2007 - Algebraic inversion of an artificial neural network classifier [Details]
Marc Schoenauer
  • ESANN 2018 - Fast Power system security analysis with Guided Dropout [Details]
  • ESANN 2019 - LEAP nets for power grid perturbations [Details]
T. Schoenauer
  • ESANN 2002 - PCNN neurocomputers - Event driven and parallel architectures [Details]
Thomas Scholten
  • ESANN 2020 - A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction [Details]
Ingo Scholtes
  • ESANN 2025 - Network Science Meets AI: A Converging Frontier [Details]
M. Scholz
  • ESANN 2002 - Nonlinear PCA: a new hierarchical approach [Details]
Lambert Schomaker
  • ESANN 2017 - Hyper-spectral frequency selection for the classification of vegetation diseases [Details]
Crispin Schomers
  • ESANN 2024 - Predicting the Closing Cross Auction Results at the NASDAQ Stock Exchange [Details]
Christoph Schommer
  • ESANN 2019 - Topic-based historical information selection for personalized sentiment analysis [Details]
Ralf Schönherr
  • ESANN 2018 - Self-learning assembly systems during ramp-up [Details]
Lea Schönherr
  • ESANN 2023 - On the Limitations of Model Stealing with Uncertainty Quantification Models [Details]
Marie Schouterden
  • ESANN 2025 - Exploring Model Architectures for Real-Time Lung Sound Event Detection [Details]
Dieter Schramm
  • ESANN 2021 - AGLVQ - Making Generalized Vector Quantization Algorithms Aware of Context [Details]
Benjamin Schrauwen
  • ESANN 2005 - Isolated word recognition using a Liquid State Machine [Details]
  • ESANN 2006 - Linking non-binned spike train kernels to several existing spike train metrics [Details]
  • ESANN 2006 - Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic [Details]
  • ESANN 2007 - Adapting reservoir states to get Gaussian distributions [Details]
  • ESANN 2007 - An overview of reservoir computing: theory, applications and implementations [Details]
  • ESANN 2007 - Bat echolocation modelling using spike kernels with Support Vector Regression. [Details]
  • ESANN 2008 - Pruning and Regularisation in Reservoir Computing: a First Insight [Details]
  • ESANN 2009 - Non-markovian process modelling with Echo State Networks [Details]
  • ESANN 2009 - Recent advances in efficient learning of recurrent networks [Details]
  • ESANN 2010 - Extending reservoir computing with random static projections: a hybrid between extreme learning and RC [Details]
  • ESANN 2010 - Machine Learning Techniques based on Random Projections [Details]
  • ESANN 2012 - A discrete/rhythmic pattern generating RNN [Details]