Publications

2023

F. Contreras, R. Peletier and K. Bunte

Proc. of the 31th European Symposium on Artificial Neural Networks (ESANN), eds. Michel Verleysen, Bruges (Belgium) and online event

Improved LAAT strategy to recover manifolds embedded in strong noise

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M. Shumska and K. Bunte

Proc. of the 31th European Symposium on Artificial Neural Networks (ESANN), eds. Michel Verleysen, Bruges (Belgium) and online event

Multispectral Texture Classification in Agriculture

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M. Marcantoni, B. Jayawardhana and K. Bunte

IEEE Control Systems Letters

Range-Only Bearing Estimator for Localization and Mapping

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M. Marcantoni, B. Jayawardhana, M. P. Chaher and K. Bunte

IEEE Control Systems Letters, vol. 7, pp. 395-400

Secure Formation Control via Edge Computing Enabled by Fully Homomorphic Encryption and Mixed Uniform-Logarithmic Quantization

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P. Awad, R. Peletier, M. Canducci, R. Smith, A. Taghribi, M. Mohammadi, J. Shin, P. Tiňo and et al

Monthly Notices of the Royal Astronomical Society, vol. 520 (3), pp. 4517-4539

Swarm Intelligence-based Extraction and Manifold Crawling Along the Large-Scale Structure

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2022

M. Canducci, P. Awad, A. Taghribi, M. Mohammadi, M. Mastropietro, Sven De Rijcke, R. F. Peletier, R. Smith and et al

Astronomy and Computing, pp. 100658

1-DREAM: 1D Recovery, Extraction and Analysis of Manifolds in noisy environments

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G. Luimstra and K. Bunte

Proc. of the 30th European Symposium on Artificial Neural Networks (ESANN), eds. Michel Verleysen, Bruges (Belgium) and online event, pp. 61-66

Adaptive Gabor Filters for Interpretable Color Texture Classification

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M. Straat, K. Koster, N. Goet and K. Bunte

2022 International Joint Conference on Neural Networks (IJCNN), Padua, Italy, pp. 01-08

An Industry 4.0 example: real-time quality control for steel-based mass production using Machine Learning on non-invasive sensor data

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M. Mohammadi, J. Mutatiinaa, T. Saifollahi and K. Bunte

Astronomy and Computing, vol. 39, pp. 100555

Detection of extragalactic Ultra-Compact Dwarfs and Globular Clusters using Explainable AI techniques

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A. Taghribi, K. Bunte, R. Smith, J. Shin, M. Mastropietro, R. F. Peletier and P. Tiňo

IEEE Transactions on Knowledge and Data Engineering

LAAT: Locally Aligned Ant Technique for discovering multiple faint low dimensional structures of varying density

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2021

A. Taghribi, M. Canducci, M. Mastropietro, Sven De Rijcke, K. Bunte and P. Tiňo

Neurocomputing, vol. 470, pp. 376-388

ASAP - A sub-sampling approach for preserving topological structures modeled with geodesic topographic mapping

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M. Mohammadi, P. Tiňo and K. Bunte

Neural Computation

Manifold Alignment Aware Ants: a Markovian process for manifold extraction

Notes: accepted for publication

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M. Canducci, A. Taghribi, M. Mastropietro, S. d. Rijcke, R. Peletier, K. Bunte and P. Tino

Intelligent Data Engineering and Automated Learning - IDEAL 2021, eds. Yin, Hujun and Camacho, David and Tino, Peter and Allmendinger, Richard and Tallón-Ballesteros, Antonio J. and Tang, Ke and Cho, Sung-Bae and Novais, Paulo and Nascimento, Susana, Cham, pp. 493-501

Tracking the Temporal-Evolution of Supernova Bubbles in Numerical Simulations

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2020

L. Oneto, K. Bunte and A. Sperduti

Neurocomputing, vol. 416, pp. 172-176

Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2019)

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A. Taghribi, K. Bunte, M. Mastropietro, S. D. Rijcke and P. Tiño

Proc. of the 28th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, pp. 67-72

ASAP - A Sub-sampling Approach for Preserving Topological Structures

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M. Mohammadi and K. Bunte

Intelligent Data Engineering and Automated Learning - IDEAL 2020, eds. Analide, Cesar and Novais, Paulo and Camacho, David and Yin, Hujun, Cham, pp. 12-24

Multi-agent Based Manifold Denoising

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R. Pauli, P. Tiño, J. C. Rogers, R. Baker, R. Clanton, P. Birch, A. Brown, G. Daniel and et al

Development and Psychopathology

Positive and Negative Parenting in Conduct Disorder with High versus Low Levels of Callous-Unemotional Traits

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S. Ghosh, P. Tiño and K. Bunte

International Joint Conference on Neural Networks (IJCNN), Glasgow, United Kingdom, pp. 1-8

Visualization and knowledge discovery from interpretable models

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2019

L. Onetto, K. Bunte and F. Schleif

Neurocomputing, vol. 342, pp. 1-5

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)

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J. Bakker and K. Bunte

Proc. of the 27th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, pp. 119-124

Efficient learning of email similarities for customer support

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M. Mohammadi, N. Petkov, K. Bunte, R. Peletier and F. Schleif

Neurocomputing, vol. 342, pp. 164-171

Globular cluster detection in the GAIA survey

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E. Baranowski, S. Ghosh, C. H. Shackleton, A. E. Taylor, B. A. Hughes, L. C. Gilligan, A. Utari, S. M. Faradz and et al

Endocrine Abstracts

Steroid metabolomics: a rapid computational approach for accurate differentiation of inborn disorders of steroidogenesis

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2018

M. Mohammadi, N. Petkov, R. Peletier, P. Bibiloni and K. Bunte

Frontiers in Artificial Intelligence and Applications (FAIA), pp. 70-78

Detection of Globular Clusters in the Halo of Milky Way

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M. Mohammadi, R. F. Peletier, F.M. Schleif, N. Petkov and K. Bunte

Neurocomputing

Globular cluster detection in the Gaia survey

Notes: accepted for publication

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M. Mohammadi, R. F. Peletier, F.M. Schleif, N. Petkov and K. Bunte

Proc. of the 26th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, pp. 327-332

Globular cluster detection in the Gaia survey

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K. Bunte, D. J. Smith, M. J. Chappell, Z. K. Hassan-Smith, J. W. Tomlinson, W. Arlt and P. Tino

Journal of Theoretical Biology, vol. 455, pp. 222-231

Learning Pharmacokinetic Models for in vivo Glucocorticoid Activation

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M. Biehl, K. Bunte, G. Longo and P. Tiño

Machine Learning and Data Analysis in Astroinformatics

Notes: Special Session at ESANN 2018 : Machine Learning and Data Analysis in Astroinformatics ; Conference date: 25-04-2018 Through 27-04-2018

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E. S. Baranowski, S. Ghosh, C. H. Shackleton, A. E. Taylor, B. A. Hughes, M. Biehl, T. Guran, K. Bunte and et al

Steroid Metabolomics: A Powerful Technique for Differentiating Inborn Disorders of Steroidogenesis

Notes: Poster presented at the 17thInternational Congress on Hormonal Steroids and Hormones & Cancer (ICHSCH) by co-supervised external PhD student Elizabeth Baranowski

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2017

Mehmet Gönen, B. A. Weir, G. S. Cowley, F. Vazquez, Y. Guan, A. Jaiswal, M. Karasuyama, V. Uzunangelov and et al

Cell Systems, vol. 5 (5), pp. 485-497.e3

A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines

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S. Ghosh, E. S. Baranowski, R. v. Veen, G. d. Vries, M. Biehl, W. Arlt, P. Tino, K. Bunte and et al

Proc. of the 25th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 177-186

Comparison of strategies to learn from imbalanced classes for computer aided diagnosis of inborn steroidogenic disorders

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E. Baranowski, K. Bunte, C. H. Shackleton, A. E. Taylor, B. A. Hughes, M. Biehl, P. Tino, T. Guran and et al

Endocrine Abstracts

Steroid metabolomics for accurate and rapid diagnosis of inborn steroidogenic disorders

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2016

F. Aiolli, K. Bunte, R. Hérault and M. Kanevski

Neurocomputing, vol. 192, pp. 1-2

Advances in artificial neural networks, machine learning and computational intelligence Selected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015)

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S. Sieberts, F. Zhu, J. García-García, E. Stahl, A. Pratap, G. Pandey, D. Pappas, D. Aguilar and et al

Nature Communications, vol. 7 (12460)

Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

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K. Bunte, M. Kaden and F. Schleif

Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 11th International Workshop WSOM, eds. Merényi, Erzsébet and Mendenhall, J. Michael and O'Driscoll, Patrick, Houston, Texas, USA, pp. 341-353

Low-Rank Kernel Space Representations in Prototype Learning

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K. Bunte, P. Tino and W. Arlt

Relevance learning vector quantization in variable dimensional spaces

Notes: Patent GB 1615330.6

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K. Bunte, E. S. Baranowski, W. Arlt and P. Tino

New Challenges in Neural Computation (NC²), eds. Barbara Hammer and Thomas Martinetz and Thomas Villmann, Hannover, Germany, pp. 20-23

Relevance Learning Vector Quantization in Variable Dimensional Spaces

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K. Bunte, E. Leppäaho, I. Saarinen and S. Kaski

Bioinformatics, vol. 32 (16), pp. 2457-2463

Sparse group factor analysis for biclustering of multiple data sources

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E. S. Baranowski, K. Bunte, C. H. Shackleton, A. E. Taylor, B. A. Hughes, M. Biehl, P. Tino, T. Guran and et al

Society for Endocrinology BES 2016

Steroid metabolomics for diagnosis of inborn steroidogenic disorders - bridging the gap between clinician and scientist through computational approaches

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2015

D. Archambault, K. Bunte, M. Á. Carreira-Perpiñán, D. Ebert, T. Ertl and B. Zupan

Dagstuhl Reports: Bridging Information Visualization with Machine Learning (Dagstuhl Seminar 15101), vol. 5, pp. 7

4.2 Machine Learning Meets Visualization: A Roadmap for Scalable Data Analytics

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J. A. Lee and K. Bunte

Unsupervised dimensionality reduction: the challenge of big data visualisation

Notes: Special Session at ESANN 2015 : Unsupervised dimensionality reduction: the challenge of big data visualisation ; Conference date: 22-04-2015 Through 24-04-2015

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2014

M. Strickert, K. Bunte, F. Schleif and E. Hüllermeier

Neurocomputing, vol. 141, pp. 97-109

Correlation-based embedding of pairwise score data

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K. Bunte, M. Järvisalo, J. Berg, P. Myllymäki, J. Peltonen and S. Kaski

Proc. of the 28th Conference on Artificial Intelligence (AAAI), eds. Carla E. Brodley and Peter Stone, Québec, Canada, pp. 1694-1700

Optimal neighborhood preserving visualization by maximum satisfiability

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2013

I. Giotis, K. Bunte, N. Petkov and M. Biehl

Journal of Mathematical Imaging and Vision, vol. 47 (1), pp. 79-92

Adaptive Matrices and Filters for Color Texture Classification

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M. Biehl, K. Bunte and P. Schneider

PLOS ONE, vol. 8 (3), pp. e59401

Analysis of Flow Cytometry Data by Matrix Relevance Learning Vector Quantization

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N. Aghaeepour, G. Finak, FlowCAP Consortium, DREAM Consortium, H. Hoos, T. R. Mosmann, R. Brinkman, R. Gottardo and et al

Nature Methods, vol. 10 (3), pp. 228-238

Critical assessment of automated flow cytometry data analysis techniques

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M. Strickert and K. Bunte

Proc. of the 21th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 77-82

Soft Rank Neighbor Embeddings

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2012

K. Bunte, M. Biehl and B. Hammer

Neural Computation, vol. 24 (3), pp. 771-804

A General Framework for Dimensionality-Reducing Data Visualization Mapping

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K. Bunte

Künstliche Intelligenz, vol. 26 (4), pp. 417-418

Adaptive Dissimilarity Measures, Dimension Reduction and Visualization (University of Groningen)

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K. Bunte, F. Schleif and M. Biehl

Proc. of the 20th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 387-392

Adaptive learning for complex-valued data

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A. Schulz, A. Gisbrecht, K. Bunte and B. Hammer

New Challenges in Neural Computation (NC²), eds. Barbara Hammer and Thomas Villmann, Graz, Austria, pp. 73-83

How to visualize a classifier?

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M. Biehl, K. Bunte, B. Hammer, F. Schleif, P. Schneider and T. Villmann

Proc. of the International Joint Conference on Neural Networks (IJCNN), eds. Hussein Abbass, Daryl Essam and Ruhul Sarker, Brisbane, Australia, pp. 1873-1880

Large Margin Linear Discriminative Visualization by Matrix Relevance Learning

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K. Bunte, P. Schneider, B. Hammer, F. Schleif, T. Villmann and M. Biehl

Neural Networks, vol. 26 (4), pp. 159-173

Limited Rank Matrix Learning - Discriminative Dimension Reduction and Visualization

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K. Bunte, S. Haase, M. Biehl and T. Villmann

Neurocomputing, vol. 90 (1), pp. 23-45

Stochastic Neighbor Embedding (SNE) for Dimension Reduction and Visualization using arbitrary Divergences

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M. B. Huber, K. Bunte, M. B. Nagarajan, M. Biehl, L. A. Ray and A. Wismüller

Artificial Intelligence in Medicine, vol. 56 (2), pp. 91-97

Texture Feature Ranking with Relevance Learning to Classify Interstitial Lung Disease Patterns

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G. Peters, K. Bunte, M. Strickert, M. Biehl and T. Villmann

Proc. of the 3rd Workshop on Trustworthy Self-Organizing Systems (TSOS), Paris, France, pp. 244-249

Visualization of Processes in Self-Learning Systems

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2011

B. Hammer, M. Biehl, K. Bunte and B. Mokbel

Advances in Self-Organizing Maps, WSOM 2011, eds. Jorma Laaksonen and Timo Honkela, pp. 277-287

A general framework for dimensionality reduction for large data sets

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K. Bunte, I. Giotis, N. Petkov and M. Biehl

14th International Conference on Computer Analysis of Images and Patterns (CAIP), Seville, Spain, pp. 489-497

Adaptive Matrices for Color Texture Classification

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K. Bunte, M. Biehl and B. Hammer

IEEE Symposium Series in Computational Intelligence (SSCI) 2011: Computational Intelligence and Data Mining (CIDM), Paris, France, pp. 349-356

Dimensionality reduction mappings

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K. Bunte, M. Biehl, M. F. Jonkman and N. Petkov

Pattern Recognition, vol. 44 (9), pp. 1892-1902

Learning effective color features for content based image retrieval in dermatology

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K. Bunte, F. Schleif, S. Haase and T. Villmann

Proc. of the 19th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 29-34

Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization

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K. Bunte, B. Hammer, T. Villmann, M. Biehl and A. Wismüller

Neurocomputing, vol. 74 (9), pp. 1340-1350

Neighbor Embedding XOM for Dimension Reduction and Visualization

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K. Bunte, M. Biehl and B. Hammer

Proc. of the 19th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 281-286

Supervised dimension reduction mappings

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M. B. Huber, K. Bunte, M. B. Nagarajan, M. Biehl, L. A. Ray and A. Wismüller

SPIE Medical Imaging: Computer-Aided Diagnosis, eds. Ronald M. Summers M.D. and Bram van Ginneken

Texture feature selection with relevance learning to classify interstitial lung disease patterns

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G. Papari, K. Bunte and M. Biehl

Waypoint averaging and step size control in learning by gradient descent

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2010

K. Bunte, B. Hammer, A. Wismüller and M. Biehl

Neurocomputing, vol. 73 (7-9), pp. 1074-1092

Adaptive Local Dissimilarity Measures for Discriminative Dimension Reduction of Labeled Data

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K. Bunte, B. Hammer, T. Villmann, M. Biehl and A. Wismüller

Proc. of the 18th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 87-92

Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization

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K. Bunte, S. Haase, M. Biehl and T. Villmann

Mathematical Foundations of Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization

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P. Schneider, K. Bunte, B. Hammer and M. Biehl

IEEE Transactions on Neural Networks, vol. 21 (5), pp. 831-840

Regularization in Matrix Relevance Learning

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B. Hammer, K. Bunte and M. Biehl

Learning paradigms in dynamic environments, eds. B. Hammer and P. Hitzler and W. Maas and M. Toussaint, pp. 15

Some steps towards a general principle for dimensionality reduction mappings

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2009

K. Bunte, M. Biehl, N. Petkov and M. F. Jonkman

Proc. of the 17th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 129-134

Adaptive Metrics for Content Based Image Retrieval in Dermatology

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K. Bunte, B. Hammer and M. Biehl

13th International Conference on Computer Analysis of Images and Patterns (CAIP), eds. Xiaoyi Jiang and Nicolai Petkov, Münster, Germany, pp. 1162-1170

Nonlinear Dimension Reduction and Visualization of Labeled Data

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K. Bunte, B. Hammer, P. Schneider and M. Biehl

Proc. of the 17th European Symposium on Artificial Neural Networks (ESANN), eds. M. Verleysen, Bruges, Belgium, pp. 65-70

Nonlinear Discriminative Data Visualization

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2008

K. Bunte, P. Schneider, B. Hammer, F. Schleif, T. Villmann and M. Biehl

Discriminative Visualization by Limited Rank Matrix Learning

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P. Schneider, K. Bunte, B. Hammer, T. Villmann and M. Biehl

Regularization in matrix relevance learning

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2007

T. Hermann, K. Bunte and H. Ritter

Proc. of the 13th International Conference on Auditory Display (ICAD), Montréal, Canada, pp. 26-29

Relevance-based Interactive Optimization of Sonification

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