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

A probability theoretic approach to drifting data in continuous time domains. - Fabian Hinder; André Artelt; Barbara Hammer (CoRR, 2019)

Explaining Concept Drift by Mean of Direction. - Fabian Hinder; Johannes Kummert; Barbara Hammer (ICANN (1), 2020)

Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD). - Fabian Hinder; André Artelt; Barbara Hammer (ICML, 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)

Counterfactual Explanations of Concept Drift. - Fabian Hinder; Barbara Hammer (CoRR, 2020)

Analysis of Drifting Features. - Fabian Hinder; Jonathan Jakob; Barbara Hammer (CoRR, 2020)

Feature relevance determination for ordinal regression in the context of feature redundancies and privileged information. - Lukas Pfannschmidt; Jonathan Jakob; Fabian Hinder; Michael Biehl; Peter Tiño; Barbara Hammer (Neurocomputing, 2020)

Concept Drift Segmentation via Kolmogorov-Trees. - Fabian Hinder; Barbara Hammer (ESANN, 2021)

Contrastive Explanations for Explaining Model Adaptations. - André Artelt; Fabian Hinder; Valerie Vaquet; Robert Feldhans; Barbara Hammer (IWANN (1), 2021)

Evaluating Robustness of Counterfactual Explanations. - André Artelt; Valerie Vaquet; Riza Velioglu; Fabian Hinder; Johannes Brinkrolf; Malte Schilling; Barbara Hammer (SSCI, 2021)

A Shape-Based Method for Concept Drift Detection and Signal Denoising. - Fabian Hinder; Johannes Brinkrolf; Valerie Vaquet; Barbara Hammer (SSCI, 2021)

Fast Non-Parametric Conditional Density Estimation using Moment Trees. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (SSCI, 2021)

Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings. - Valerie Vaquet; Fabian Hinder; Jonas Vaquet; Johannes Brinkrolf; Barbara Hammer (SSCI, 2021)

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

Federated learning vector quantization for dealing with drift between nodes. - Johannes Brinkrolf; Valerie Vaquet; Fabian Hinder; Patrick Menz; Udo Seiffert; Barbara Hammer (ESANN, 2022)

Contrasting Explanation of Concept Drift. - Fabian Hinder; André Artelt; Valerie Vaquet; Barbara Hammer (ESANN, 2022)

Feature Selection for Trustworthy Regression Using Higher Moments. - Fabian Hinder; Johannes Brinkrolf; Barbara Hammer (ICANN (4), 2022)

Suitability of Different Metric Choices for Concept Drift Detection. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (IDA, 2022)

Localization of Concept Drift: Identifying the Drifting Datapoints. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; André Artelt; Barbara Hammer (IJCNN, 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)

Precise Change Point Detection using Spectral Drift Detection. - Fabian Hinder; André Artelt; Valerie Vaquet; Barbara Hammer (CoRR, 2022)

On the Change of Decision Boundaries and Loss in Learning with Concept Drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (CoRR, 2022)

Feature Selection for Concept Drift Detection. - Fabian Hinder; Barbara Hammer (ESANN, 2023)

On the Hardness and Necessity of Supervised Concept Drift Detection. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (ICPRAM, 2023)

On the Change of Decision Boundary and Loss in Learning with Concept Drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (IDA, 2023)

Combining self-labeling and demand based active learning for non-stationary data streams. - Valerie Vaquet; Fabian Hinder; Johannes Brinkrolf; Barbara Hammer (CoRR, 2023)

One or Two Things We know about Concept Drift - A Survey on Monitoring Evolving Environments. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (CoRR, 2023)

Localization of Small Leakages in Water Distribution Networks using Concept Drift Explanation Methods. - Valerie Vaquet; Fabian Hinder; Kathrin Lammers; Jonas Vaquet; Barbara Hammer (CoRR, 2023)

Model-based explanations of concept drift. - Fabian Hinder; Valerie Vaquet; Johannes Brinkrolf; Barbara Hammer (Neurocomputing, 2023)

Contrasting Explanations for Understanding and Regularizing Model Adaptations. - André Artelt; Fabian Hinder; Valerie Vaquet; Robert Feldhans; Barbara Hammer (Neural Process. Lett., 2023)

Causes of Rejects in Prototype-based Classification Aleatoric vs. Epistemic Uncertainty. - Johannes Brinkrolf; Valerie Vaquet; Fabian Hinder; Barbara Hammer (ESANN, 2024)

On the Fine Structure of Drifting Features. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (ESANN, 2024)

Self-Supervised Learning from Incrementally Drifting Data Streams. - Valerie Vaquet; Jonas Vaquet; Fabian Hinder; Kleanthis Malialis; Christos G. Panayiotou; Marios M. Polycarpou; Barbara Hammer (ESANN, 2024)

Challenges, Methods, Data-A Survey of Machine Learning in Water Distribution Networks. - Valerie Vaquet; Fabian Hinder; André Artelt; Inaam Ashraf; Janine Strotherm; Jonas Vaquet; Johannes Brinkrolf; Barbara Hammer (ICANN (9), 2024)

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

Investigating the Suitability of Concept Drift Detection for Detecting Leakages in Water Distribution Networks. - Valerie Vaquet; Fabian Hinder; Barbara Hammer (ICPRAM, 2024)

A Remark on Concept Drift for Dependent Data. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (IDA (1), 2024)

Localizing of Anomalies in Critical Infrastructure using Model-Based Drift Explanations. - Valerie Vaquet; Fabian Hinder; Jonas Vaquet; Kathrin Lammers; Lars Quakernack; Barbara Hammer (IJCNN, 2024)

FairGLVQ: Fairness in Partition-Based Classification. - Felix Störck; Fabian Hinder; Johannes Brinkrolf; Benjamin Paassen; Valerie Vaquet; Barbara Hammer (WSOM+, 2024)

Adversarial Attacks for Drift Detection. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (CoRR, 2024)

An Algorithm-Centered Approach To Model Streaming Data. - Fabian Hinder; Valerie Vaquet; David Komnick; Barbara Hammer (CoRR, 2024)

One or two things we know about concept drift - a survey on monitoring in evolving environments. Part A: detecting concept drift. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (Frontiers Artif. Intell., 2024)

One or two things we know about concept drift - a survey on monitoring in evolving environments. Part B: locating and explaining concept drift. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (Frontiers Artif. Intell., 2024)

Feature-based analyses of concept drift. - Fabian Hinder; Valerie Vaquet; Barbara Hammer (Neurocomputing, 2024)

Continual Learning Should Move Beyond Incremental Classification. - Rupert Mitchell; Antonio Alliegro; Raffaello Camoriano; Dustin Carrión-Ojeda; Antonio Carta; Georgia Chalvatzaki; Nikhil Churamani; Carlo D'Eramo; Samin Hamidi; Robin Hesse; Fabian Hinder; Roshni Kamath; et al. (CoRR, 2025)

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

Causal Explanation of Concept Drift - A Truly Actionable Approach. - David Komnick; Kathrin Lammers; Barbara Hammer; Valerie Vaquet; Fabian Hinder (CoRR, 2025)