Relevance learning in generative topographic maps. - Andrej Gisbrecht; Barbara Hammer (ESANN, 2010)

Relational Generative Topographic Map. - Andrej Gisbrecht; Bassam Mokbel; Barbara Hammer (ESANN, 2010)

Visualizing Dissimilarity Data Using Generative Topographic Mapping. - Andrej Gisbrecht; Bassam Mokbel; Alexander Hasenfuss; Barbara Hammer (KI, 2010)

Accelerating kernel clustering for biomedical data analysis. - Andrej Gisbrecht; Barbara Hammer; Frank-Michael Schleif; Xibin Zhu (CIBCB, 2011)

Accelerating Kernel Neural Gas. - Frank-Michael Schleif; Andrej Gisbrecht; Barbara Hammer (ICANN (1), 2011)

Linear Time Heuristics for Topographic Mapping of Dissimilarity Data. - Andrej Gisbrecht; Frank-Michael Schleif; Xibin Zhu; Barbara Hammer (IDEAL, 2011)

Topographic Mapping of Dissimilarity Data. - Barbara Hammer; Andrej Gisbrecht; Alexander Hasenfuss; Bassam Mokbel; Frank-Michael Schleif; Xibin Zhu (WSOM, 2011)

Supervised learning of short and high-dimensional temporal sequences for life science measurements - Frank-Michael Schleif; Andrej Gisbrecht; Barbara Hammer (CoRR, 2011)

Relevance learning in generative topographic mapping. - Andrej Gisbrecht; Barbara Hammer (Neurocomputing, 2011)

Relational generative topographic mapping. - Andrej Gisbrecht; Bassam Mokbel; Barbara Hammer (Neurocomputing, 2011)

Out-of-sample kernel extensions for nonparametric dimensionality reduction. - Andrej Gisbrecht; Wouter Lueks; Bassam Mokbel; Barbara Hammer (ESANN, 2012)

Relevance learning for time series inspection. - Andrej Gisbrecht; Dusan Sovilj; Barbara Hammer; Amaury Lendasse (ESANN, 2012)

Visualizing the quality of dimensionality reduction. - Bassam Mokbel; Wouter Lueks; Andrej Gisbrecht; Michael Biehl; Barbara Hammer (ESANN, 2012)

Learning Relevant Time Points for Time-Series Data in the Life Sciences. - Frank-Michael Schleif; Bassam Mokbel; Andrej Gisbrecht; Leslie Theunissen; Volker Dürr; Barbara Hammer (ICANN (2), 2012)

Fast approximated relational and kernel clustering. - Frank-Michael Schleif; Xibin Zhu; Andrej Gisbrecht; Barbara Hammer (ICPR, 2012)

Discriminative Dimensionality Reduction Mappings. - Andrej Gisbrecht; Daniela Hofmann; Barbara Hammer (IDA, 2012)

Linear basis-function t-SNE for fast nonlinear dimensionality reduction. - Andrej Gisbrecht; Bassam Mokbel; Barbara Hammer (IJCNN, 2012)

Relevance learning for short high-dimensional time series in the life sciences. - Frank-Michael Schleif; Andrej Gisbrecht; Barbara Hammer (IJCNN, 2012)

How to Visualize Large Data Sets? - Barbara Hammer; Andrej Gisbrecht; Alexander Schulz 001 (WSOM, 2012)

Efficient Approximations of Kernel Robust Soft LVQ. - Daniela Hofmann; Andrej Gisbrecht; Barbara Hammer (WSOM, 2012)

Linear Time Relational Prototype Based Learning. - Andrej Gisbrecht; Bassam Mokbel; Frank-Michael Schleif; Xibin Zhu; Barbara Hammer (Int. J. Neural Syst., 2012)

Approximation techniques for clustering dissimilarity data. - Xibin Zhu; Andrej Gisbrecht; Frank-Michael Schleif; Barbara Hammer (Neurocomputing, 2012)

Visualizing dependencies of spectral features using mutual information. - Andrej Gisbrecht; Yoan Miché; Barbara Hammer; Amaury Lendasse (ESANN, 2013)

Discriminative Dimensionality Reduction for the Visualization of Classifiers. - Andrej Gisbrecht; Alexander Schulz 001; Barbara Hammer (ICPRAM (Selected Papers), 2013)

Applications of Discriminative Dimensionality Reduction. - Barbara Hammer; Andrej Gisbrecht; Alexander Schulz 001 (ICPRAM, 2013)

Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic Samples. - Andrej Gisbrecht; Barbara Hammer; Bassam Mokbel; Alexander Sczyrba (IV, 2013)

Using Nonlinear Dimensionality Reduction to Visualize Classifiers. - Alexander Schulz 001; Andrej Gisbrecht; Barbara Hammer (IWANN (1), 2013)

Data Analysis of (Non-)Metric Proximities at Linear Costs. - Frank-Michael Schleif; Andrej Gisbrecht (SIMBAD, 2013)

Visualizing the quality of dimensionality reduction. - Bassam Mokbel; Wouter Lueks; Andrej Gisbrecht; Barbara Hammer (Neurocomputing, 2013)

Relevance Learning for Dimensionality Reduction. - Alexander Schulz 001; Andrej Gisbrecht; Barbara Hammer (ESANN, 2014)

Innovationen für die distanzbasierte Datenvisualisierung. - Andrej Gisbrecht (Ausgezeichnete Informatikdissertationen, 2014)

Advances in dissimilarity-based data visualisation. - Andrej Gisbrecht (2015)

Probabilistic Classification Vector Machine at large scale. - Frank-Michael Schleif; Andrej Gisbrecht; Peter Tiño (ESANN, 2015)

Large Scale Indefinite Kernel Fisher Discriminant. - Frank-Michael Schleif; Andrej Gisbrecht; Peter Tiño (SIMBAD, 2015)

Metric and non-metric proximity transformations at linear costs. - Andrej Gisbrecht; Frank-Michael Schleif (Neurocomputing, 2015)

Parametric nonlinear dimensionality reduction using kernel t-SNE. - Andrej Gisbrecht; Alexander Schulz 001; Barbara Hammer (Neurocomputing, 2015)

Efficient approximations of robust soft learning vector quantization for non-vectorial data. - Daniela Hofmann; Andrej Gisbrecht; Barbara Hammer (Neurocomputing, 2015)

Using Discriminative Dimensionality Reduction to Visualize Classifiers. - Alexander Schulz 001; Andrej Gisbrecht; Barbara Hammer (Neural Process. Lett., 2015)

Data visualization by nonlinear dimensionality reduction. - Andrej Gisbrecht; Barbara Hammer (WIREs Data Mining Knowl. Discov., 2015)

Probabilistic classifiers with low rank indefinite kernels. - Frank-Michael Schleif; Andrej Gisbrecht; Peter Tiño (CoRR, 2016)

Supervised low rank indefinite kernel approximation using minimum enclosing balls. - Frank-Michael Schleif; Andrej Gisbrecht; Peter Tiño (Neurocomputing, 2018)

Graph Representation and Embedding for Semiconductor Manufacturing Fab States. - Benedikt Schulz; Christoph Jacobi; Andrej Gisbrecht; Evangelos Angelidis; Chew Wye Chan; Boon Ping Gan (WSC, 2022)

A Standard Framework for AI-Driven Optimizations in Various Complex Domains. - Tobias Bosse; Evangelos Angelidis; Feifei Zhang; Chew Wye Chan; Boon Ping Gan; Matthias Werner; Andrej Gisbrecht (WSC, 2024)