Using visual analytics to analyze movement and action patterns. - Dirk Streeb; Udo Schlegel; Juri Buchmüller; Fabian Fischer 001; Daniel A. Keim (VAST, 2015)

SIZE: Satellite Image Zooming and Exploration. - Udo Schlegel; Alexandra Diehl; Daniel A. Keim (VAST, 2017)

Uncovering the Mistford Toxic Conspiracy. - Dirk Streeb; Juri Buchmüller; Udo Schlegel; Wolfgang Jentner; Michael Behrisch 001; Bruno Schneider; Daniel Seebacher (VAST, 2017)

G-Rap: interactive text synthesis using recurrent neural network suggestions. - Udo Schlegel; Eren Cakmak; Juri Buchmüller; Daniel A. Keim (ESANN, 2018)

Interactive Classification Using Spectrograms and Audio Glyphs. - Eren Cakmak; Udo Schlegel; Matthias Miller; Juri Buchmüller; Wolfgang Jentner; Daniel A. Keim (VAST, 2018)

RescueMark: Visual Analytics of Social Media Data for Guiding Emergency Response in Disaster Situations: Award for Skillful Integration of Language Model. - Astrik Jeitler; Alpin Türkoglu; Denis Makarov; Timo Jockers; Juri Buchmüller; Udo Schlegel; Daniel A. Keim (VAST, 2019)

N.E.A.T. - Novel Emergency Analysis Tool. - Wolfgang Jentner; Juri Buchmüller; Fabian Sperrle; Rita Sevastjanova; Thilo Spinner; Udo Schlegel; Dirk Streeb; Hanna Schäfer (VAST, 2019)

Earthquake Investigation and Visual Cognizance of Multivariate Temporal Tabular Data Using Machine Learning. - Arjun Majumdar; Gent Ymeri; Sebastian Strumbelj; Juri Buchmüller; Udo Schlegel; Daniel A. Keim (VAST, 2019)

cpmViz: A Web-Based Visualization Tool for Uncertain Spatiotemporal Data. - Fabian Nagel; Giuliano Castiglia; Gemza Ademaj; Juri Buchmüller; Udo Schlegel; Daniel A. Keim (VAST, 2019)

Visual Analytics for Supporting Conflict Resolution in Large Railway Networks. - Udo Schlegel; Wolfgang Jentner; Juri Buchmüller; Eren Cakmak; Giuliano Castiglia; Renzo Canepa; Simone Petralli; Luca Oneto; Daniel A. Keim; Davide Anguita (INNSBDDL, 2019)

Towards a Rigorous Evaluation of XAI Methods on Time Series. - Udo Schlegel; Hiba Arnout; Mennatallah El-Assady; Daniela Oelke; Daniel A. Keim (CoRR, 2019)

SpatialRugs: Enhancing Spatial Awareness of Movement in Dense Pixel Visualizations. - Juri F. Buchmüller; Udo Schlegel; Eren Cakmak; Daniel A. Keim; Evanthia Dimara (EuroVA@Eurographics/EuroVis, 2020)

Towards visual debugging for multi-target time series classification. - Udo Schlegel; Eren Cakmak; Hiba Arnout; Mennatallah El-Assady; Daniela Oelke; Daniel A. Keim (IUI, 2020)

ModelSpeX: Model Specification Using Explainable Artificial Intelligence Methods. - Udo Schlegel; Eren Cakmak; Daniel A. Keim (MLVis@Eurographics/EuroVis, 2020)

An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks. - Udo Schlegel; Daniela Oelke; Daniel A. Keim; Mennatallah El-Assady (CoRR, 2020)

explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning. - Thilo Spinner; Udo Schlegel; Hanna Schäfer; Mennatallah El-Assady (IEEE Trans. Vis. Comput. Graph., 2020)

Speculative Execution of Similarity Queries: Real-Time Parameter Optimization through Visual Exploration. - Thilo Spinner; Udo Schlegel; Martin Schall; Fabian Sperrle; Rita Sevastjanova; Beatrice Gobbo; Julius Rauscher; Mennatallah El-Assady; Daniel A. Keim (EDBT/ICDT Workshops, 2021)

TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models. - Udo Schlegel; Duy Vo Lam; Daniel A. Keim; Daniel Seebacher (PKDD/ECML Workshops (1), 2021)

SpatialRugs: A compact visualization of space and time for analyzing collective movement data. - Juri F. Buchmüller; Udo Schlegel; Eren Cakmak; Daniel A. Keim; Evanthia Dimara (Comput. Graph., 2021)

Time Series Model Attribution Visualizations as Explanations. - Udo Schlegel; Daniel A. Keim (CoRR, 2021)

Multiscale Snapshots: Visual Analysis of Temporal Summaries in Dynamic Graphs. - Eren Cakmak; Udo Schlegel; Dominik Jäckle; Daniel A. Keim; Tobias Schreck (IEEE Trans. Vis. Comput. Graph., 2021)

A Comprehensive Workflow for Effective Imitation and Reinforcement Learning with Visual Analytics. - Yannick Metz; Udo Schlegel; Daniel Seebacher; Mennatallah El-Assady; Daniel A. Keim (EuroVA@EuroVis, 2022)

ViNNPruner: Visual Interactive Pruning for Deep Learning. - Udo Schlegel; Samuel Schiegg; Daniel A. Keim (MLVis@EuroVis, 2022)

Explainable AI for Time Series Classification: A Review, Taxonomy and Research Directions. - Andreas Theissler; Francesco Spinnato; Udo Schlegel; Riccardo Guidotti (IEEE Access, 2022)

Task-Based Visual Interactive Modeling: Decision Trees and Rule-Based Classifiers. - Dirk Streeb; Yannick Metz; Udo Schlegel; Bruno Schneider; Mennatallah El-Assady; Hansjörg Neth; Min Chen 001; Daniel A. Keim (IEEE Trans. Vis. Comput. Graph., 2022)

Interactive Dense Pixel Visualizations for Time Series and Model Attribution Explanations. - Udo Schlegel; Daniel A. Keim (MLVis@EuroVis, 2023)

Introducing the Attribution Stability Indicator: A Measure for Time Series XAI Attributions. - Udo Schlegel; Daniel A. Keim (PKDD/ECML Workshops (3), 2023)

ExpLIMEable: A Visual Analytics Approach for Exploring LIME. - Sonia Laguna; Julian N. Heidenreich; Jiugeng Sun; Nilüfer Cetin; Ibrahim Al Hazwani; Udo Schlegel; Furui Cheng; Mennatallah El-Assady (VAHC, 2023)

A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI. - Udo Schlegel; Daniel A. Keim (xAI (3), 2023)

Visual Explanations with Attributions and Counterfactuals on Time Series Classification. - Udo Schlegel; Daniela Oelke; Daniel A. Keim; Mennatallah El-Assady (CoRR, 2023)

Searching Temporally Distant Activities in Lifelog Data With PraK Tool V2. - Zuzana Vopálková; Jakub Yaghob; Michael Stroh; Udo Schlegel; Jakub Lokoc (LSC@ICMR, 2024)

PraK Tool: An Interactive Search Tool Based on Video Data Services. - Jakub Lokoc; Zuzana Vopálková; Michael Stroh; Raphael Buchmueller; Udo Schlegel (MMM (4), 2024)

Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics. - Lukas Klein; Carsten T. Lüth; Udo Schlegel; Till J. Bungert; Mennatallah El-Assady; Paul F. Jaeger (NeurIPS, 2024)

Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series. - Udo Schlegel; Daniel A. Keim; Tobias Sutter (TempXAI@PKDD/ECML, 2024)

VAST 2024-MC2 Challenge. - Funda Yildiz Aydin; Mehmet Emre Sahin; Sinem Bilge Güler; Udo Schlegel; Daniel A. Keim (VAST Challenge@VIS, 2024)

Fishing Vizzard: An Interactive Visual Analytics Tool to Identify Suspicious Fishing Behavior. - Antonella Bidlingmaier; Julian Jandeleit; Fred Kunze; Lisa-Maria Reutlinger; Tolga Tuncer; Udo Schlegel; Daniel A. Keim (VAST Challenge@VIS, 2024)

Visual Bias Detection for Addressing Illegal Fishing Activities. - Raphael Buchmüller; Daniel Fürst; Alexander Frings; Udo Schlegel; Daniel A. Keim (VAST Challenge@VIS, 2024)

Interactive Counterfactual Generation for Univariate Time Series. - Udo Schlegel; Julius Rauscher; Daniel A. Keim (CoRR, 2024)

Leveraging Color Channel Independence for Improved Unsupervised Object Detection. - Bastian Jäckl; Yannick Metz; Udo Schlegel; Daniel A. Keim; Maximilian T. Fischer (CoRR, 2024)

Visually Assessing 1-D Orderings of Contiguous Spatial Polygons. - Julius Rauscher; Frederik L. Dennig; Udo Schlegel; Daniel A. Keim; Johannes Fuchs 001 (Comput. Graph. Forum, 2025)

Which LIME should I trust? Concepts, Challenges, and Solutions. - Patrick Knab; Sascha Marton; Udo Schlegel; Christian Bartelt (CoRR, 2025)

My Answer Is NOT 'Fair': Mitigating Social Bias in Vision-Language Models via Fair and Biased Residuals. - Jian Lan; Yifei Fu; Udo Schlegel; Gengyuan Zhang; Tanveer Hannan; Haokun Chen; Thomas Seidl 001 (CoRR, 2025)

Towards Explainable Deep Clustering for Time Series Data. - Udo Schlegel; Gabriel Marques Tavares; Thomas Seidl 001 (CoRR, 2025)