Kerstin Bunte

Orcid: 0000-0002-2930-6172

Affiliations:
  • University of Groningen, Bernoulli Institute, The Netherlands


According to our database1, Kerstin Bunte authored at least 56 papers between 2009 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
LAAT: Locally Aligned Ant Technique for Discovering Multiple Faint Low Dimensional Structures of Varying Density.
IEEE Trans. Knowl. Data Eng., June, 2023

Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization.
IEEE Control. Syst. Lett., 2023

Range-Only Bearing Estimator for Localization and Mapping.
IEEE Control. Syst. Lett., 2023

Towards Robust Colour Texture Classification with Limited Training Data.
Proceedings of the Computer Analysis of Images and Patterns, 2023

2022
Manifold Alignment Aware Ants: A Markovian Process for Manifold Extraction.
Neural Comput., 2022

ASAP - A sub-sampling approach for preserving topological structures modeled with geodesic topographic mapping.
Neurocomputing, 2022

Advances in artificial neural networks, machine learning and computational intelligence.
Neurocomputing, 2022

Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets.
CoRR, 2022

Detection of extragalactic Ultra-compact dwarfs and Globular Clusters using Explainable AI techniques.
Astron. Comput., 2022

1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments.
Astron. Comput., 2022

An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data.
Proceedings of the International Joint Conference on Neural Networks, 2022

Adaptive Gabor Filters for Interpretable Color Texture Classification.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2021, 2021

2020
Advances in artificial neural networks, machine learning and computational intelligence.
Neurocomputing, 2020

LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density.
CoRR, 2020

Visualisation and knowledge discovery from interpretable models.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Multi-agent Based Manifold Denoising.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2020, 2020

ASAP - A Sub-sampling Approach for Preserving Topological Structures.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019
Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26<sup><i>th</i></sup> European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018).
Neurocomputing, 2019

Globular cluster detection in the GAIA survey.
Neurocomputing, 2019

Efficient learning of email similarities for customer support.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

2018
Machine learning and data analysis in astroinformatics.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Detection of Globular Clusters in the Halo of Milky Way.
Proceedings of the Applications of Intelligent Systems, 2018

2017
Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

2016
Special issue: Advances in artificial neural networks, machine learning and computational intelligenceSelected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015).
Neurocomputing, 2016

Sparse group factor analysis for biclustering of multiple data sources.
Bioinform., 2016

Low-Rank Kernel Space Representations in Prototype Learning.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2016

2015
Unsupervised dimensionality reduction: the challenge of big data visualization.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Erratum to: Adaptive Matrices and Filters for Color Texture Classification.
J. Math. Imaging Vis., 2014

Correlation-based embedding of pairwise score data.
Neurocomputing, 2014

Optimal Neighborhood Preserving Visualization by Maximum Satisfiability.
Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014

2013
Adaptive Matrices and Filters for Color Texture Classification.
J. Math. Imaging Vis., 2013

Soft rank neighbor embeddings.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Limited Rank Matrix Learning, discriminative dimension reduction and visualization.
Neural Networks, 2012

A General Framework for Dimensionality-Reducing Data Visualization Mapping.
Neural Comput., 2012

Adaptive Dissimilarity Measures, Dimension Reduction and Visualization (University of Groningen).
Künstliche Intell., 2012

Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences.
Neurocomputing, 2012

Texture feature ranking with relevance learning to classify interstitial lung disease patterns.
Artif. Intell. Medicine, 2012

Visualization of processes in self-learning systems.
Proceedings of the Tenth Annual International Conference on Privacy, Security and Trust, 2012

Large margin linear discriminative visualization by Matrix Relevance Learning.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Adaptive learning for complex-valued data.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
Learning effective color features for content based image retrieval in dermatology.
Pattern Recognit., 2011

Neighbor embedding XOM for dimension reduction and visualization.
Neurocomputing, 2011

A General Framework for Dimensionality Reduction for Large Data Sets.
Proceedings of the Advances in Self-Organizing Maps - 8th International Workshop, 2011

Texture feature selection with relevance learning to classify interstitial lung disease patterns.
Proceedings of the Medical Imaging 2011: Computer-Aided Diagnosis, 2011

Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Supervised dimension reduction mappings.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Dimensionality reduction mappings.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011

Adaptive Matrices for Color Texture Classification.
Proceedings of the Computer Analysis of Images and Patterns, 2011

2010
Regularization in matrix relevance learning.
IEEE Trans. Neural Networks, 2010

Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data.
Neurocomputing, 2010

Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization.
Proceedings of the 18th European Symposium on Artificial Neural Networks, 2010

Some steps towards a general principle for dimensionality reduction mappings.
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010

2009
Nonlinear Discriminative Data Visualization.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Adaptive Metrics for Content Based Image Retrieval in Dermatology.
Proceedings of the 17th European Symposium on Artificial Neural Networks, 2009

Nonlinear Dimension Reduction and Visualization of Labeled Data.
Proceedings of the Computer Analysis of Images and Patterns, 13th International Conference, 2009


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