Towards Understanding Mobility in Museums. - Golnaz Elmamooz; Bettina Finzel; Daniela Nicklas 001 (BTW (Workshops), 2017)

From beliefs to intention: mentoring as an approach to motivate female high school students to enrol in computer science studies. - Bettina Finzel; Hannah Deininger; Ute Schmid (GenderIT, 2018)

Verifying Deep Learning-based Decisions for Facial Expression Recognition. - Ines Rieger; Rene Kollmann; Bettina Finzel; Dominik Seuss; Ute Schmid (ESANN, 2020)

Uncovering the Bias in Facial Expressions. - Jessica Deuschel; Bettina Finzel; Ines Rieger (CoRR, 2020)

The Next Generation of Medical Decision Support: A Roadmap Toward Transparent Expert Companions. - Sebastian Bruckert; Bettina Finzel; Ute Schmid (Frontiers Artif. Intell., 2020)

Mutual Explanations for Cooperative Decision Making in Medicine. - Ute Schmid; Bettina Finzel (Künstliche Intell., 2020)

Multimodal Explanations for User-centric Medical Decision Support Systems. - Bettina Finzel; David Elias Tafler; Anna Magdalena Thaler; Ute Schmid (HUMAN@AAAI Fall Symposium, 2021)

Explanation as a Process: User-Centric Construction of Multi-level and Multi-modal Explanations. - Bettina Finzel; David E. Tafler; Stephan Scheele; Ute Schmid (KI, 2021)

Deriving Temporal Prototypes from Saliency Map Clusters for the Analysis of Deep-Learning-based Facial Action Unit Classification. - Bettina Finzel; René Kollmann; Ines Rieger; Jaspar Pahl; Ute Schmid (LWDA, 2021)

XAI Method Properties: A (Meta-)study. - Gesina Schwalbe; Bettina Finzel (CoRR, 2021)

CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition. - Ines Rieger; Jaspar Pahl; Bettina Finzel; Ute Schmid (ICPR, 2022)

Explaining with Attribute-Based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust. - Bettina Finzel; Simon P. Kuhn; David E. Tafler; Ute Schmid (ILP, 2022)

Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs. - Bettina Finzel; Anna Saranti; Alessa Angerschmid; David E. Tafler; Bastian Pfeifer; Andreas Holzinger (Künstliche Intell., 2022)

Domain-Specific Evaluation of Visual Explanations for Application-Grounded Facial Expression Recognition. - Bettina Finzel; Ines Rieger; Simon Kuhn; Ute Schmid (CD-MAKE, 2023)

Toward human-level concept learning: Pattern benchmarking for AI algorithms. - Andreas Holzinger; Anna Saranti; Alessa Angerschmid; Bettina Finzel; Ute Schmid; Heimo Müller (Patterns, 2023)

Near Hit and Near Miss Example Explanations for Model Revision in Binary Image Classification. - Bettina Finzel; Judith Knoblach; Anna Magdalena Thaler; Ute Schmid (IDEAL (2), 2024)

When a Relation Tells More Than a Concept: Exploring and Evaluating Classifier Decisions with CoReX. - Bettina Finzel; Patrick Hilme; Johannes Rabold; Ute Schmid (CoRR, 2024)

A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts. - Gesina Schwalbe; Bettina Finzel (Data Min. Knowl. Discov., 2024)

Human-Centered Explanations: Lessons Learned from Image Classification for Medical and Clinical Decision Making. - Bettina Finzel (Künstliche Intell., 2024)

Toward Simple and Robust Contrastive Explanations for Image Classification by Leveraging Instance Similarity and Concept Relevance. - Yuliia Kaidashova; Bettina Finzel; Ute Schmid (KI, 2025)

Re-evaluating the Robustness and Interpretability of the Contrastive Explanations Method for Image Classification. - Luisa Schneider; Bettina Finzel; Ute Schmid (KI, 2025)

Toward trustworthy AI with integrative explainable AI frameworks. - Bettina Finzel (it Inf. Technol., 2025)