Nonlinear Dimension Reduction and Visualization of Labeled Data. - Kerstin Bunte; Barbara Hammer; Michael Biehl (CAIP, 2009)

Adaptive Metrics for Content Based Image Retrieval in Dermatology. - Kerstin Bunte; Michael Biehl; Nicolai Petkov; Marcel F. Jonkman (ESANN, 2009)

Nonlinear Discriminative Data Visualization. - Kerstin Bunte; Barbara Hammer; Petra Schneider; Michael Biehl (ESANN, 2009)

Some steps towards a general principle for dimensionality reduction mappings. - Barbara Hammer; Kerstin Bunte; Michael Biehl (Learning paradigms in dynamic environments, 2010)

Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization. - Kerstin Bunte; Barbara Hammer; Thomas Villmann; Michael Biehl; Axel Wismüller (ESANN, 2010)

Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data. - Kerstin Bunte; Barbara Hammer; Axel Wismüller; Michael Biehl (Neurocomputing, 2010)

Regularization in matrix relevance learning. - Petra Schneider; Kerstin Bunte; Han Stiekema; Barbara Hammer; Thomas Villmann; Michael Biehl (IEEE Trans. Neural Networks, 2010)

Adaptive Matrices for Color Texture Classification. - Kerstin Bunte; Ioannis Giotis 002; Nicolai Petkov; Michael Biehl (CAIP (2), 2011)

Dimensionality reduction mappings. - Kerstin Bunte; Michael Biehl; Barbara Hammer (CIDM, 2011)

Supervised dimension reduction mappings. - Kerstin Bunte; Michael Biehl; Barbara Hammer (ESANN, 2011)

Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization. - Kerstin Bunte; Frank-Michael Schleif; Sven Haase; Thomas Villmann (ESANN, 2011)

Texture feature selection with relevance learning to classify interstitial lung disease patterns. - Markus B. Huber; Kerstin Bunte; Mahesh B. Nagarajan; Michael Biehl; Lawrence A. Ray; Axel Wismüller (Computer-Aided Diagnosis, 2011)

A General Framework for Dimensionality Reduction for Large Data Sets. - Barbara Hammer; Michael Biehl; Kerstin Bunte; Bassam Mokbel (WSOM, 2011)

Neighbor embedding XOM for dimension reduction and visualization. - Kerstin Bunte; Barbara Hammer; Thomas Villmann; Michael Biehl; Axel Wismüller (Neurocomputing, 2011)

Learning effective color features for content based image retrieval in dermatology. - Kerstin Bunte; Michael Biehl; Marcel F. Jonkman; Nicolai Petkov (Pattern Recognit., 2011)

Adaptive learning for complex-valued data. - Kerstin Bunte; Frank-Michael Schleif; Michael Biehl (ESANN, 2012)

Large margin linear discriminative visualization by Matrix Relevance Learning. - Michael Biehl; Kerstin Bunte; Frank-Michael Schleif; Petra Schneider; Thomas Villmann (IJCNN, 2012)

Visualization of processes in self-learning systems. - Gabriele Peters; Kerstin Bunte; Marc Strickert; Michael Biehl; Thomas Villmann (PST, 2012)

Texture feature ranking with relevance learning to classify interstitial lung disease patterns. - Markus B. Huber; Kerstin Bunte; Mahesh B. Nagarajan; Michael Biehl; Lawrence A. Ray; Axel Wismüller (Artif. Intell. Medicine, 2012)

Stochastic neighbor embedding (SNE) for dimension reduction and visualization using arbitrary divergences. - Kerstin Bunte; Sven Haase; Michael Biehl; Thomas Villmann (Neurocomputing, 2012)

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

A General Framework for Dimensionality-Reducing Data Visualization Mapping. - Kerstin Bunte; Michael Biehl; Barbara Hammer (Neural Comput., 2012)

Limited Rank Matrix Learning, discriminative dimension reduction and visualization. - Kerstin Bunte; Petra Schneider; Barbara Hammer; Frank-Michael Schleif; Thomas Villmann; Michael Biehl (Neural Networks, 2012)

Soft rank neighbor embeddings. - Marc Strickert; Kerstin Bunte (ESANN, 2013)

Adaptive Matrices and Filters for Color Texture Classification. - Ioannis Giotis 002; Kerstin Bunte; Nicolai Petkov; Michael Biehl (J. Math. Imaging Vis., 2013)

Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. - Kerstin Bunte; Matti Järvisalo; Jeremias Berg; Petri Myllymäki; Jaakko Peltonen; Samuel Kaski (AAAI, 2014)

Correlation-based embedding of pairwise score data. - Marc Strickert; Kerstin Bunte; Frank-Michael Schleif; Eyke Hüllermeier (Neurocomputing, 2014)

Erratum to: Adaptive Matrices and Filters for Color Texture Classification. - Ioannis Giotis 002; Kerstin Bunte; Nicolai Petkov; Michael Biehl (J. Math. Imaging Vis., 2014)

Unsupervised dimensionality reduction: the challenge of big data visualization. - Kerstin Bunte; John Aldo Lee (ESANN, 2015)

Low-Rank Kernel Space Representations in Prototype Learning. - Kerstin Bunte; Marika Kaden; Frank-Michael Schleif (WSOM, 2016)

Sparse group factor analysis for biclustering of multiple data sources. - Kerstin Bunte; Eemeli Leppäaho; Inka Saarinen; Samuel Kaski (Bioinform., 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). - Fabio Aiolli; Kerstin Bunte; Romain Hérault; Mikhail F. Kanevski (Neurocomputing, 2016)

Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders. - Sreejita Ghosh; Elizabeth Sarah Baranowski; Rick van Veen; Gert-Jan de Vries; Michael Biehl; Wiebke Arlt; Peter Tiño; Kerstin Bunte (ESANN, 2017)

Detection of Globular Clusters in the Halo of Milky Way. - Mohammad Mohammadi 004; Nicolai Petkov; Reynier F. Peletier; Pedro Bibiloni; Kerstin Bunte (APPIS, 2018)

Machine learning and data analysis in astroinformatics. - Michael Biehl; Kerstin Bunte; Giuseppe Longo; Peter Tiño (ESANN, 2018)

Efficient learning of email similarities for customer support. - Jelle Bakker; Kerstin Bunte (ESANN, 2019)

Globular cluster detection in the GAIA survey. - Mohammad Mohammadi 004; Nicolai Petkov; Kerstin Bunte; Reynier F. Peletier; Frank-Michael Schleif (Neurocomputing, 2019)

Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). - Luca Oneto; Kerstin Bunte; Frank-Michael Schleif (Neurocomputing, 2019)

ASAP - A Sub-sampling Approach for Preserving Topological Structures. - Abolfazl Taghribi; Kerstin Bunte; Michele Mastropietro; Sven De Rijcke; Peter Tiño (ESANN, 2020)

Multi-agent Based Manifold Denoising. - Mohammad Mohammadi 004; Kerstin Bunte (IDEAL (2), 2020)

Visualisation and knowledge discovery from interpretable models. - Sreejita Ghosh; Peter Tiño; Kerstin Bunte (IJCNN, 2020)

LAAT: Locally Aligned Ant Technique for detecting manifolds of varying density. - Abolfazl Taghribi; Kerstin Bunte; Rory Smith; Jihye Shin; Michele Mastropietro; Reynier F. Peletier; Peter Tiño (CoRR, 2020)

Advances in artificial neural networks, machine learning and computational intelligence. - Luca Oneto; Kerstin Bunte; Alessandro Sperduti (Neurocomputing, 2020)

Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations. - Marco Canducci; Abolfazl Taghribi; Michele Mastropietro; Sven De Rijcke; Reynier Peletier; Kerstin Bunte; Peter Tino (IDEAL, 2021)

Adaptive Gabor Filters for Interpretable Color Texture Classification. - Gerrit Luimstra; Kerstin Bunte (ESANN, 2022)

An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data. - Michiel Straat; Kevin Koster; Nick Goet; Kerstin Bunte (IJCNN, 2022)

1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments. - Marco Canducci; P. Awad; Abolfazl Taghribi; Mohammad Mohammadi 004; Michele Mastropietro; Sven De Rijcke; Reynier Peletier; Rory Smith; Kerstin Bunte; Peter Tiño (Astron. Comput., 2022)

Detection of extragalactic Ultra-compact dwarfs and Globular Clusters using Explainable AI techniques. - Mohammad Mohammadi 004; Jarvin Mutatiina; Teymoor Saifollahi; Kerstin Bunte (Astron. Comput., 2022)

Interpretable Models Capable of Handling Systematic Missingness in Imbalanced Classes and Heterogeneous Datasets. - Sreejita Ghosh; Elizabeth Sarah Baranowski; Michael Biehl; Wiebke Arlt; Peter Tino; Kerstin Bunte (CoRR, 2022)

Advances in artificial neural networks, machine learning and computational intelligence. - Luca Oneto; Kerstin Bunte; Nicolò Navarin (Neurocomputing, 2022)

ASAP - A sub-sampling approach for preserving topological structures modeled with geodesic topographic mapping. - Abolfazl Taghribi; Marco Canducci; Michele Mastropietro; Sven De Rijcke; Kerstin Bunte; Peter Tino (Neurocomputing, 2022)

Manifold Alignment Aware Ants: A Markovian Process for Manifold Extraction. - Mohammad Mohammadi 004; Peter Tino; Kerstin Bunte (Neural Comput., 2022)

Towards Robust Colour Texture Classification with Limited Training Data. - Mariya Shumska; Kerstin Bunte (CAIP (1), 2023)

Improved the locally aligned ant technique (LAAT) strategy to recover manifolds embedded in strong noise. - Felipe Contreras; Kerstin Bunte; Reynier Peletier (ESANN, 2023)

Multispectral Texture Classification in Agriculture. - Mariya Shumska; Kerstin Bunte (ESANN, 2023)

Range-Only Bearing Estimator for Localization and Mapping. - Matteo Marcantoni; Bayu Jayawardhana; Kerstin Bunte (IEEE Control. Syst. Lett., 2023)

Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization. - Matteo Marcantoni; Bayu Jayawardhana; Mariano Perez Chaher; Kerstin Bunte (IEEE Control. Syst. Lett., 2023)

LAAT: Locally Aligned Ant Technique for Discovering Multiple Faint Low Dimensional Structures of Varying Density. - Abolfazl Taghribi; Kerstin Bunte; Rory Smith; Jihye Shin; Michele Mastropietro; Reynier F. Peletier; Peter Tino (IEEE Trans. Knowl. Data Eng., 2023)

Bearing-Only Distance Estimator for Localization and Mapping. - Matteo Marcantoni; Emma Langeveld; Bayu Jayawardhana; Kerstin Bunte (CDC, 2024)

MRI-Based Head and Neck Tumor Segmentation Using nnU-Net with 15-Fold Cross-Validation Ensemble. - Frank N. Mol; Luuk van der Hoek; Baoqiang Ma; Bharath Chowdhary Nagam; Nanna Maria Sijtsema; Lisanne van Dijk; Kerstin Bunte; Rifka Vlijm; Peter M. A. van Ooijen (HNTS-MRG@MICCAI, 2024)

Towards Robust Colour Texture Analysis with Limited Training Data. - Mariya Shumska; Michael H. F. Wilkinson; Kerstin Bunte (SN Comput. Sci., 2024)

More than a void? The detection and characterization of cavities in a simulated galaxy's interstellar medium. - Abolfazl Taghribi; Marco Canducci; Michele Mastropietro; Sven De Rijcke; Reynier Frans Peletier; Peter Tino; Kerstin Bunte (Astron. Comput., 2025)

Interpretable modelling and visualization of biomedical data. - Sreejita Ghosh; Elizabeth Sarah Baranowski; Michael Biehl; Wiebke Arlt; Peter Tiño; Kerstin Bunte (Neurocomputing, 2025)

On the importance of structural identifiability for machine learning with partially observed dynamical systems. - Janis Norden; Elisa Oostwal; Michael Chappell; Peter Tino; Kerstin Bunte (CoRR, 2025)