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
Frank Köster
  • ESANN 2023 - Potential analysis of a Quantum RL controller in the context of autonomous driving [Details]
  • ESANN 2026 - Revisiting Neural Activation Coverage for Uncertainty Estimation [Details]
W. A. Kosters
  • ESANN 1997 - Two neural network methods for multidimensional scaling [Details]
W.A. Kosters
  • ESANN 2000 - A Bayesian approach to combined neural networks forecasting [Details]
T. Kostiainen
  • ESANN 2000 - Self-Organizing Maps in data analysis - notes on overfitting and overinterpretation [Details]
Oleh Kostromin
  • ESANN 2025 - RAM: Retrieval Augmented Modelling for Tabular In-Context Few-Shot Domain Adaptation [Details]
N'Dah Jean Kouagou
  • ESANN 2026 - A Possible Human-Centered Embedding Space Search in Degenerate Clifford Algebras [Details]
Patrick Kouontchou
  • ESANN 2007 - ICA-based High Frequency VaR for Risk Management [Details]
  • ESANN 2009 - A wavelet-heterogeneous index of market shocks for assessing the magnitude of financial crises [Details]
  • ESANN 2013 - Forecasting Financial Markets with Classified Tactical Signals [Details]
  • ESANN 2015 - Towards a Tomographic Index of Systemic Risk Measures [Details]
O. Kouropteva
  • ESANN 2003 - Classification of handwritten digits using supervised locally linear embedding algorithm and support vector machine [Details]
György Kovács
  • ESANN 2020 - Cross-Encoded Meta Embedding towards Transfer Learning [Details]
Boris Kovalerchuk
  • ESANN 2004 - Neural networks for data mining: constrains and open problems [Details]
W. Kowalczyk
  • ESANN 1996 - An algorithm for training multilayer networks on non-numerical data [Details]
Jan Koza
  • No papers found
Jan Koza
  • ESANN 2022 - Neural-network-based estimation of normal distributions in black-box optimization [Details]
Ryszard Kozera
  • ESANN 2023 - Performance Evaluation of Activation Functions in Extreme Learning Machine [Details]
Wojciech Kozlowski
  • ESANN 2009 - Application of SVM for cell recognition in BCC skin pathology [Details]
Oliver Kramer
  • ESANN 2020 - Learning Step Size Adaptation in Evolution Strategies [Details]
  • ESANN 2020 - Tournament Selection Improves Cartesian Genetic Programming for Atari Games [Details]
  • ESANN 2021 - Evolutionary Deep Multi-Task Learning [Details]
  • ESANN 2021 - Transformers for Molecular Graph Generation [Details]
  • ESANN 2022 - A Fast and Simple Evolution Strategy with Covariance Matrix Estimation [Details]
  • ESANN 2023 - Enhancing Evolution Strategies with Evolution Path Bias [Details]
  • ESANN 2023 - Wind Power Prediction with ETSformer [Details]
  • ESANN 2024 - LLaMA Tunes CMA-ES [Details]
  • ESANN 2024 - Towards Explainable Evolution Strategies with Large Language Models [Details]
  • ESANN 2025 - Unlocking Structured Thinking in Language Models with Cognitive Prompting [Details]
  • ESANN 2026 - LMAP: Local PCA Models with Global MDS Embeddings [Details]
  • ESANN 2026 - Linear Evaluation Complexity of Surrogate-Assisted (1+1)-EA on OneMax [Details]
Oliver Kramer
  • ESANN 2015 - Comparison of Numerical Models and Statistical Learning for Wind Speed Prediction [Details]
  • ESANN 2015 - Supervised Manifold Learning with Incremental Stochastic Embeddings [Details]
  • ESANN 2018 - Properties of adv−1 – Adversarials of Adversarials [Details]
Oliver Kramer
  • ESANN 2020 - Adversarials-1 in Speech Recognition: Detection and Defence [Details]
Marie Kratz
  • ESANN 2005 - Stochastic analysis of the Abe formulation of Hopfield networks [Details]
A. Kravetski
  • ESANN 2000 - Application of MLP and stochastic simulations for electricity load forecasting in Russia [Details]
Alexander Krawczyk
  • ESANN 2025 - Continual Unlearning through Memory Suppression [Details]
A. Krawiecki
  • ESANN 1998 - On-off intermittency in small neural networks with synaptic noise [Details]
B. Krekelberg
  • ESANN 1993 - A lateral inhibition neural network that emulates a winner-takes-all algorithm [Details]
Dominik Krenzer
  • ESANN 2025 - The Reinforced Liquid State Machine: A New Training Architecture for Spiking Neural Networks [Details]
U. Kressel
  • ESANN 1999 - Dimensionality reduction by local processing [Details]
Nils Morten Kriege
  • ESANN 2019 - Deep Weisfeiler-Lehman assignment kernels via multiple kernel learning [Details]
Hans-Peter Kriegel
  • ESANN 2007 - Spiral Recurrent Neural Network for Online Learning [Details]
Catherine Krier
  • ESANN 2007 - Feature clustering and mutual information for the selection of variables in spectral data [Details]
  • ESANN 2009 - Supervised variable clustering for classification of NIR spectra [Details]
Evan Kriminger
  • ESANN 2012 - One-class classifier based on extreme value statistics [Details]
Agathoklis Krimpenis
  • ESANN 2005 - Initialisation improvement in engineering feedforward ANN models [Details]