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

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)

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

Valid interpretation of feature relevance for linear data mappings. - Benoît Frénay; Daniela Hofmann; Alexander Schulz 001; Michael Biehl; Barbara Hammer (CIDM, 2014)

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

Visualization of Regression Models Using Discriminative Dimensionality Reduction. - Alexander Schulz 001; Barbara Hammer (CAIP (2), 2015)

Unsupervised Dimensionality Reduction for Transfer Learning. - Patrick Blöbaum; Alexander Schulz 001; Barbara Hammer (ESANN, 2015)

Metric Learning in Dimensionality Reduction. - Alexander Schulz 001; Barbara Hammer (ICPRAM (1), 2015)

Discriminative dimensionality reduction for regression problems using the Fisher metric. - Alexander Schulz 001; Barbara Hammer (IJCNN, 2015)

Inferring Feature Relevances From Metric Learning. - Alexander Schulz 001; Bassam Mokbel; Michael Biehl; Barbara Hammer (SSCI, 2015)

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

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

Discriminative dimensionality reduction in kernel space. - Alexander Schulz 001; Barbara Hammer (ESANN, 2016)

Echo State Networks as Novel Approach for Low-Cost Myoelectric Control. - Cosima Prahm; Alexander Schulz 001; Benjamin Paaßen; Oskar Aszmann; Barbara Hammer; Georg Dorffner (AIME, 2017)

An EM transfer learning algorithm with applications in bionic hand prostheses. - Benjamin Paassen; Alexander Schulz 001; Janne Hahne; Barbara Hammer (ESANN, 2017)

Linear supervised transfer learning for the large margin nearest neighbor classifier. - Kolja Berger; Alexander Schulz 001; Benjamin Paaßen; Barbara Hammer (SSCI, 2017)

Efficient kernelisation of discriminative dimensionality reduction. - Alexander Schulz 001; Johannes Brinkrolf; Barbara Hammer (Neurocomputing, 2017)

Discriminative dimensionality reduction: variations, applications, interpretations - Alexander Schulz 001 (2017)

Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto. - Alexander Schulz 001; Jeffrey Frederic Queißer; Hisashi Ishihara; Minoru Asada (ICDL-EPIROB, 2018)

Expectation maximization transfer learning and its application for bionic hand prostheses. - Benjamin Paaßen; Alexander Schulz 001; Janne Hahne; Barbara Hammer (Neurocomputing, 2018)

DeepView: Visualizing the behavior of deep neural networks in a part of the data space. - Alexander Schulz 001; Fabian Hinder; Barbara Hammer (CoRR, 2019)

Reservoir memory machines. - Benjamin Paassen; Alexander Schulz 001 (ESANN, 2020)

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction. - Alexander Schulz 001; Fabian Hinder; Barbara Hammer (IJCAI, 2020)

Evaluating Metrics for Bias in Word Embeddings. - Sarah Schröder; Alexander Schulz 001; Philip Kenneweg; Robert Feldhans; Fabian Hinder; Barbara Hammer (CoRR, 2021)

Efficient Reject Options for Particle Filter Object Tracking in Medical Applications. - Johannes Kummert; Alexander Schulz 001; Tim Redick; Nassim Ayoub; Ali Modabber; Dirk Abel; Barbara Hammer (Sensors, 2021)

Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers. - Philip Kenneweg; Alexander Schulz 001; Sarah Schröder; Barbara Hammer (IDEAL, 2022)

BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models. - Lisa Langnickel; Alexander Schulz 001; Barbara Hammer; Juliane Fluck (CoRR, 2022)

The SAME score: Improved cosine based bias score for word embeddings. - Sarah Schröder; Alexander Schulz 001; Philip Kenneweg; Robert Feldhans; Fabian Hinder; Barbara Hammer (CoRR, 2022)

Reservoir stack machines. - Benjamin Paaßen; Alexander Schulz 001; Barbara Hammer (Neurocomputing, 2022)

Reservoir Memory Machines as Neural Computers. - Benjamin Paaßen; Alexander Schulz 001; Terrence C. Stewart; Barbara Hammer (IEEE Trans. Neural Networks Learn. Syst., 2022)

One-Class Intrusion Detection with Dynamic Graphs. - Aleksei Liuliakov; Alexander Schulz 001; Luca Hermes; Barbara Hammer (ICANN (4), 2023)

"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction. - André Artelt; Alexander Schulz 001; Barbara Hammer (ICPRAM, 2023)

Debiasing Sentence Embedders Through Contrastive Word Pairs. - Philip Kenneweg; Sarah Schröder; Alexander Schulz 001; Barbara Hammer (ICPRAM, 2023)

So Can We Use Intrinsic Bias Measures or Not? - Sarah Schröder; Alexander Schulz 001; Philip Kenneweg; Barbara Hammer (ICPRAM, 2023)

Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation. - Sarah Schröder; Alexander Schulz 001; Ivan Tarakanov; Robert Feldhans; Barbara Hammer (IWANN (1), 2023)

Extending Drift Detection Methods to Identify When Exactly the Change Happened. - Markus Vieth; Alexander Schulz 001; Barbara Hammer (IWANN (1), 2023)

Data Augmentation for Cardiovascular Time Series Data Using WaveNet. - Robert Feldhans; Alexander Schulz 001; Johannes Kummert; Moriz Habigt; Maike Stemmler; Christina Kohler; Dirk Abel; Rolf Rossaint; Barbara Hammer (SSCI, 2023)

Generating Cardiovascular Data to Improve Training of Assistive Heart Devices. - Johannes Kummert; Alexander Schulz 001; Robert Feldhans; Moriz Habigt; Maike Stemmler; Christina Kohler; Dirk Abel; Rolf Rossaint; Barbara Hammer (SSCI, 2023)

Metric Learning with Self-Adjusting Memory for Explaining Feature Drift. - Johannes Kummert; Alexander Schulz 001; Barbara Hammer (SN Comput. Sci., 2023)

Predicting the Level of Co-Activation of One Muscle Head from the Other Muscle Head of the Biceps Brachii Muscle by Linear Regression and Shallow Feedforward Neural Networks. - Nils Grimmelsmann; Malte Mechtenberg; Markus Vieth; Alexander Schulz 001; Barbara Hammer; Axel Schneider (BIOSTEC (1), 2024)

Generation Gap or Diffusion Trap? How Age Affects the Detection of Personalized AI-Generated Images. - René Lüdemann; Alexander Schulz 001; Ulrike Kuhl (CHIRA (2), 2024)

Noise Robust One-Class Intrusion Detection on Dynamic Graphs. - Aleksei Liuliakov; Alexander Schulz 001; Luca Hermes; Barbara Hammer (ESANN, 2024)

Visualizing and Improving 3D Mesh Segmentation with DeepView. - Andreas Mazur; Isaac Roberts; David P. Leins; Alexander Schulz 001; Barbara Hammer (ESANN, 2024)

Semantic Properties of Cosine Based Bias Scores for Word Embeddings. - Sarah Schröder; Alexander Schulz 001; Fabian Hinder; Barbara Hammer (ICPRAM, 2024)

The SAME score: Improved cosine based measure for semantic bias. - Sarah Schröder; Alexander Schulz 001; Barbara Hammer (IJCNN, 2024)

Targeted Visualization of the Backbone of Encoder LLMs. - Isaac Roberts; Alexander Schulz 001; Luca Hermes; Barbara Hammer (CoRR, 2024)

Conceptualizing Uncertainty. - Isaac Roberts; Alexander Schulz 001; Sarah Schröder; Fabian Hinder; Barbara Hammer (CoRR, 2025)