Kerstin Bunte

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 36

Top Topics

Unsupervised Dimensionality Reduction

Machine Learning

Texture Classification

Artificial Neural Networks

Top Venues

IEEE Control. Syst. Lett.

Publications

Mariya Shumska, Michael H. F. Wilkinson, Kerstin Bunte
Towards Robust Colour Texture Analysis with Limited Training Data. SN Comput. Sci. 5 (6) (2024)
Matteo Marcantoni, Bayu Jayawardhana, Kerstin Bunte
Range-Only Bearing Estimator for Localization and Mapping. IEEE Control. Syst. Lett. 7 (2023)
Abolfazl Taghribi, Kerstin Bunte, Rory Smith, Jihye Shin, Michele Mastropietro, Reynier F. Peletier, Peter Tino
LAAT: Locally Aligned Ant Technique for Discovering Multiple Faint Low Dimensional Structures of Varying Density. IEEE Trans. Knowl. Data Eng. 35 (6) (2023)
Matteo Marcantoni, Bayu Jayawardhana, Mariano Perez Chaher, Kerstin Bunte
Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization. IEEE Control. Syst. Lett. 7 (2023)
Mariya Shumska, Kerstin Bunte
Towards Robust Colour Texture Classification with Limited Training Data. CAIP (1) (2023)
Felipe Contreras, Kerstin Bunte, Reynier Peletier
Improved the locally aligned ant technique (LAAT) strategy to recover manifolds embedded in strong noise. ESANN (2023)
Matteo Marcantoni, Bayu Jayawardhana, Kerstin Bunte
Range-Only Bearing Estimator for Localization and Mapping. CoRR (2023)
Mariya Shumska, Kerstin Bunte
Multispectral Texture Classification in Agriculture. ESANN (2023)
Mohammad Mohammadi, Jarvin Mutatiina, Teymoor Saifollahi, Kerstin Bunte
Detection of extragalactic Ultra-Compact Dwarfs and Globular Clusters using Explainable AI techniques. CoRR (2022)
Matteo Marcantoni, Bayu Jayawardhana, Mariano Perez Chaher, Kerstin Bunte
Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization. CoRR (2022)
Gerrit Luimstra, Kerstin Bunte
Adaptive Gabor Filters for Interpretable Color Texture Classification. ESANN (2022)
Luca Oneto, Kerstin Bunte, Nicolò Navarin
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 470 (2022)
Sreejita Ghosh, Elizabeth Sarah Baranowski, Michael Biehl, Wiebke Arlt, Peter Tino, Kerstin Bunte
Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets. CoRR (2022)
Abolfazl Taghribi, Marco Canducci, Michele Mastropietro, Sven De Rijcke, Kerstin Bunte, Peter Tino
ASAP - A sub-sampling approach for preserving topological structures modeled with geodesic topographic mapping. Neurocomputing 470 (2022)
Mohammad Mohammadi, Jarvin Mutatiina, Teymoor Saifollahi, Kerstin Bunte
Detection of extragalactic Ultra-compact dwarfs and Globular Clusters using Explainable AI techniques. Astron. Comput. 39 (2022)
Marco Canducci, P. Awad, Abolfazl Taghribi, Mohammad Mohammadi, Michele Mastropietro, Sven De Rijcke, Reynier Peletier, Rory Smith, Kerstin Bunte, Peter Tiño
1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments. Astron. Comput. 41 (2022)
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data. CoRR (2022)
Michiel Straat, Kevin Koster, Nick Goet, Kerstin Bunte
An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data. IJCNN (2022)
Mohammad Mohammadi, Peter Tino, Kerstin Bunte
Manifold Alignment Aware Ants: A Markovian Process for Manifold Extraction. Neural Comput. 34 (3) (2022)
Marco Canducci, Abolfazl Taghribi, Michele Mastropietro, Sven De Rijcke, Reynier Peletier, Kerstin Bunte, Peter Tino
Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations. IDEAL (2021)
Mohammad Mohammadi, Kerstin Bunte
Multi-agent Based Manifold Denoising. IDEAL (2) (2020)
Sreejita Ghosh, Peter Tiño, Kerstin Bunte
Visualisation and knowledge discovery from interpretable models. IJCNN (2020)
Abolfazl Taghribi, Kerstin Bunte, Rory Smith, Jihye Shin, Michele Mastropietro, Reynier F. Peletier, Peter Tiño
LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density. CoRR (2020)
Abolfazl Taghribi, Kerstin Bunte, Michele Mastropietro, Sven De Rijcke, Peter Tiño
ASAP - A Sub-sampling Approach for Preserving Topological Structures. ESANN (2020)
Sreejita Ghosh, Peter Tiño, Kerstin Bunte
Visualisation and knowledge discovery from interpretable models. CoRR (2020)
Luca Oneto, Kerstin Bunte, Alessandro Sperduti
Advances in artificial neural networks, machine learning and computational intelligence. Neurocomputing 416 (2020)
Jelle Bakker, Kerstin Bunte
Efficient learning of email similarities for customer support. ESANN (2019)
Mohammad Mohammadi, Nicolai Petkov, Kerstin Bunte, Reynier F. Peletier, Frank-Michael Schleif
Globular cluster detection in the GAIA survey. Neurocomputing 342 (2019)
Luca Oneto, Kerstin Bunte, Frank-Michael Schleif
European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). Neurocomputing 342 (2019)
Mohammad Mohammadi, Nicolai Petkov, Reynier F. Peletier, Pedro Bibiloni, Kerstin Bunte
Detection of Globular Clusters in the Halo of Milky Way. APPIS (2018)
Mohammad Mohammadi, Reynier Peletier, Frank-Michael Schleif, Nicolai Petkov, Kerstin Bunte
Globular Cluster Detection in the Gaia Survey. ESANN (2018)
Michael Biehl, Kerstin Bunte, Giuseppe Longo, Peter Tiño
Machine learning and data analysis in astroinformatics. ESANN (2018)
Sreejita Ghosh, Elizabeth Sarah Baranowski, Rick van Veen, Gert-Jan de Vries, Michael Biehl, Wiebke Arlt, Peter Tiño, Kerstin Bunte
Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. ESANN (2017)
Kerstin Bunte, Marika Kaden, Frank-Michael Schleif
Low-Rank Kernel Space Representations in Prototype Learning. WSOM (2016)
Fabio Aiolli, Kerstin Bunte, Romain Hérault, Mikhail F. Kanevski
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 192 (2016)
Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen, Samuel Kaski
Sparse group factor analysis for biclustering of multiple data sources. Bioinform. 32 (16) (2016)
Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen, Samuel Kaski
Sparse group factor analysis for biclustering of multiple data sources. CoRR (2015)
Kerstin Bunte, John Aldo Lee
Unsupervised dimensionality reduction: the challenge of big data visualization. ESANN (2015)
Marc Strickert, Kerstin Bunte, Frank-Michael Schleif, Eyke Hüllermeier
Correlation-based embedding of pairwise score data. Neurocomputing 141 (2014)
Kerstin Bunte, Matti Järvisalo, Jeremias Berg, Petri Myllymäki, Jaakko Peltonen, Samuel Kaski
Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. AAAI (2014)
Ioannis Giotis, Kerstin Bunte, Nicolai Petkov, Michael Biehl
Erratum to: Adaptive Matrices and Filters for Color Texture Classification. J. Math. Imaging Vis. 48 (1) (2014)
Marc Strickert, Kerstin Bunte
Soft rank neighbor embeddings. ESANN (2013)
Ioannis Giotis, Kerstin Bunte, Nicolai Petkov, Michael Biehl
Adaptive Matrices and Filters for Color Texture Classification. J. Math. Imaging Vis. 47 (1-2) (2013)
Kerstin Bunte
Adaptive Dissimilarity Measures, Dimension Reduction and Visualization (University of Groningen). Künstliche Intell. 26 (4) (2012)
Kerstin Bunte, Michael Biehl, Barbara Hammer
A General Framework for Dimensionality-Reducing Data Visualization Mapping. Neural Comput. 24 (3) (2012)
Kerstin Bunte, Frank-Michael Schleif, Michael Biehl
Adaptive learning for complex-valued data. ESANN (2012)
Kerstin Bunte, Sven Haase, Michael Biehl, Thomas Villmann
Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences. Neurocomputing 90 (2012)
Markus B. Huber, Kerstin Bunte, Mahesh B. Nagarajan, Michael Biehl, Lawrence A. Ray, Axel Wismüller
Texture feature ranking with relevance learning to classify interstitial lung disease patterns. Artif. Intell. Medicine 56 (2) (2012)
Gabriele Peters, Kerstin Bunte, Marc Strickert, Michael Biehl, Thomas Villmann
Visualization of processes in self-learning systems. PST (2012)
Michael Biehl, Kerstin Bunte, Frank-Michael Schleif, Petra Schneider, Thomas Villmann
Large margin linear discriminative visualization by Matrix Relevance Learning. IJCNN (2012)
Kerstin Bunte, Petra Schneider, Barbara Hammer, Frank-Michael Schleif, Thomas Villmann, Michael Biehl
Limited Rank Matrix Learning, discriminative dimension reduction and visualization. Neural Networks 26 (2012)
Barbara Hammer, Michael Biehl, Kerstin Bunte, Bassam Mokbel
A General Framework for Dimensionality Reduction for Large Data Sets. WSOM (2011)
Kerstin Bunte, Michael Biehl, Barbara Hammer
Supervised dimension reduction mappings. ESANN (2011)
Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller
Neighbor embedding XOM for dimension reduction and visualization. Neurocomputing 74 (9) (2011)
Markus B. Huber, Kerstin Bunte, Mahesh B. Nagarajan, Michael Biehl, Lawrence A. Ray, Axel Wismüller
Texture feature selection with relevance learning to classify interstitial lung disease patterns. Medical Imaging: Computer-Aided Diagnosis (2011)
Kerstin Bunte, Frank-Michael Schleif, Sven Haase, Thomas Villmann
Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. ESANN (2011)
Kerstin Bunte, Michael Biehl, Marcel F. Jonkman, Nicolai Petkov
Learning effective color features for content based image retrieval in dermatology. Pattern Recognit. 44 (9) (2011)
Kerstin Bunte, Michael Biehl, Barbara Hammer
Dimensionality reduction mappings. CIDM (2011)
Kerstin Bunte, Ioannis Giotis, Nicolai Petkov, Michael Biehl
Adaptive Matrices for Color Texture Classification. CAIP (2) (2011)
Kerstin Bunte, Barbara Hammer, Axel Wismüller, Michael Biehl
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data. Neurocomputing 73 (7-9) (2010)
Petra Schneider, Kerstin Bunte, Han Stiekema, Barbara Hammer, Thomas Villmann, Michael Biehl
Regularization in matrix relevance learning. IEEE Trans. Neural Networks 21 (5) (2010)
Barbara Hammer, Kerstin Bunte, Michael Biehl
Some steps towards a general principle for dimensionality reduction mappings. Learning paradigms in dynamic environments (2010)
Kerstin Bunte, Barbara Hammer, Thomas Villmann, Michael Biehl, Axel Wismüller
Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. ESANN (2010)
Kerstin Bunte, Michael Biehl, Nicolai Petkov, Marcel F. Jonkman
Adaptive Metrics for Content Based Image Retrieval in Dermatology. ESANN (2009)
Kerstin Bunte, Barbara Hammer, Petra Schneider, Michael Biehl
Nonlinear Discriminative Data Visualization. ESANN (2009)
Kerstin Bunte, Barbara Hammer, Michael Biehl
Nonlinear Dimension Reduction and Visualization of Labeled Data. CAIP (2009)