Ute Schmid

ORCID

Publication Activity (10 Years)

Years Active: 1997-2024
Publications (10 Years): 101

Top Venues

CoRR

Künstliche Intell.

Dagstuhl Reports

Technical University of Berlin, Germany (PHD)

Education History

Technical University of Berlin, Germany

PHD

Publications

Bettina Finzel, Patrick Hilme, Johannes Rabold, Ute Schmid
When a Relation Tells More Than a Concept: Exploring and Evaluating Classifier Decisions with CoReX. CoRR (2024)
Franz Motzkus, Georgii Mikriukov, Christian Hellert, Ute Schmid
Locally Testing Model Detections for Semantic Global Concepts. CoRR (2024)
Franz Motzkus, Christian Hellert, Ute Schmid
CoLa-DCE - Concept-guided Latent Diffusion Counterfactual Explanations. CoRR (2024)
Simon Schramm, Christoph Wehner, Ute Schmid
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey. CoRR (2024)
Emanuel Slany, Stephan Scheele, Ute Schmid
Hybrid Explanatory Interactive Machine Learning for Medical Diagnosis. AIAI (1) (2024)
Jonas Troles, Ute Schmid, Wen Fan, Jiaojiao Tian
BAMFORESTS: Bamberg Benchmark Forest Dataset of Individual Tree Crowns in Very-High-Resolution UAV Images. Remote. Sens. 16 (11) (2024)
Lukas Bahr, Christoph Wehner, Judith Wewerka, José Bittencourt, Ute Schmid, Rüdiger Daub
Knowledge Graph Enhanced Retrieval-Augmented Generation for Failure Mode and Effects Analysis. CoRR (2024)
Céline Hocquette, Johannes Langer, Andrew Cropper, Ute Schmid
Can humans teach machines to code? CoRR (2024)
Simon Schramm, Christoph Wehner, Ute Schmid
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey. J. Web Semant. 79 (2023)
Lun Ai, Johannes Langer, Stephen H. Muggleton, Ute Schmid
Explanatory machine learning for sequential human teaching. Mach. Learn. 112 (10) (2023)
Joscha Eirich, Dominik Jäckle, Michael Sedlmair, Christoph Wehner, Ute Schmid, Jürgen Bernard, Tobias Schreck
ManuKnowVis: How to Support Different User Groups in Contextualizing and Leveraging Knowledge Repositories. IEEE Trans. Vis. Comput. Graph. 29 (8) (2023)
Louisa Heidrich, Emanuel Slany, Stephan Scheele, Ute Schmid
FairCaipi: A Combination of Explanatory Interactive and Fair Machine Learning for Human and Machine Bias Reduction. Mach. Learn. Knowl. Extr. 5 (4) (2023)
Simon Schramm, Ulrich Niklas, Ute Schmid
Cluster Robust Inference for Embedding-Based Knowledge Graph Completion. KSEM (1) (2023)
Bettina Finzel, Ines Rieger, Simon Kuhn, Ute Schmid
Domain-Specific Evaluation of Visual Explanations for Application-Grounded Facial Expression Recognition. CD-MAKE (2023)
Bettina Finzel, Simon P. Kuhn, David E. Tafler, Ute Schmid
Explaining with Attribute-based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust. CoRR (2023)
Jonas-Dario Troles, Richard Nieding, Sonia Simons, Ute Schmid
Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data. CoRR (2023)
Jonas Troles, Richard Nieding, Sonia Simons, Ute Schmid
Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data. I4CS (2023)
Simon Schramm, Ute Schmid
Inductive Logic Programming for Explainable Graph Clustering. ICKG (2023)
Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Bettina Finzel, Ute Schmid, Heimo Müller
Toward human-level concept learning: Pattern benchmarking for AI algorithms. Patterns 4 (8) (2023)
Luc De Raedt, Ute Schmid, Johannes Langer
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 23442). Dagstuhl Reports 13 (10) (2023)
Durgesh Nandini, Ute Schmid
Explaining Hate Speech Classification with Model Agnostic Methods. CoRR (2023)
Emanuel Slany, Stephan Scheele, Ute Schmid
Bayesian CAIPI: A Probabilistic Approach to Explanatory and Interactive Machine Learning. ECAI Workshops (1) (2023)
Ines Rieger, Jaspar Pahl, Bettina Finzel, Ute Schmid
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition. CoRR (2022)
Sebastian Kiefer, Mareike Hoffmann, Ute Schmid
Semantic Interactive Learning for Text Classification: A Constructive Approach for Contextual Interactions. Mach. Learn. Knowl. Extr. 4 (4) (2022)
Christoph Wehner, Francis Powlesland, Bashar Altakrouri, Ute Schmid
Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation. IEA/AIE (2022)
Dennis Müller, Michael März, Stephan Scheele, Ute Schmid
An Interactive Explanatory AI System for Industrial Quality Control. AAAI (2022)
Julio Wissing, Stephan Scheele, Aliya Mohammed, Dorothea Kolossa, Ute Schmid
HiMLEdge - Energy-Aware Optimization for Hierarchical Machine Learning. ARTIIS (2) (2022)
Emanuel Slany, Yannik Ott, Stephan Scheele, Jan Paulus, Ute Schmid
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification. CoRR (2022)
Ute Schmid
Constructing Explainability - Interdisciplinary Framework to Actively Shape Explanations in XAI. Künstliche Intell. 36 (3) (2022)
Gesina Schwalbe, Christian Wirth, Ute Schmid
Concept Embeddings for Fuzzy Logic Verification of Deep Neural Networks in Perception Tasks. CoRR (2022)
Durgesh Nandini, Ute Schmid
Explaining Hate Speech Classification with Model-Agnostic Methods. KI (Workshops) (2022)
Ute Schmid, Britta Wrede
Explainable AI. Künstliche Intell. 36 (3) (2022)
Dennis Müller, Michael März, Stephan Scheele, Ute Schmid
An Interactive Explanatory AI System for Industrial Quality Control. CoRR (2022)
Kyra Gobel, Cornelia Niessen, Sebastian Seufert, Ute Schmid
Explanatory machine learning for justified trust in human-AI collaboration: Experiments on file deletion recommendations. Frontiers Artif. Intell. 5 (2022)
Kolja Kühnlenz, Ute Schmid, Barbara Kühnlenz
A Video-based Study on Perceived Intelligence, Subjective Performance and Trust under Variation of Prior Information given to Users in Autonomous Driving. ARSO (2022)
Christoph Wehner, Francis Powlesland, Bashar Altakrouri, Ute Schmid
Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation. CoRR (2022)
Ute Schmid, Britta Wrede
What is Missing in XAI So Far? Künstliche Intell. 36 (3) (2022)
Bettina Finzel, Simon P. Kuhn, David E. Tafler, Ute Schmid
Explaining with Attribute-Based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust. ILP (2022)
Jaspar Pahl, Ines Rieger, Anna Möller, Thomas Wittenberg, Ute Schmid
Female, white, 27? Bias Evaluation on Data and Algorithms for Affect Recognition in Faces. FAccT (2022)
Ines Rieger, Jaspar Pahl, Bettina Finzel, Ute Schmid
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition. ICPR (2022)
Emanuel Slany, Yannik Ott, Stephan Scheele, Jan Paulus, Ute Schmid
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification. AIAI Workshops (2022)
Joscha Eirich, Jakob Bonart, Dominik Jäckle, Michael Sedlmair, Ute Schmid, Kai Fischbach, Tobias Schreck, Jürgen Bernard
IRVINE: A Design Study on Analyzing Correlation Patterns of Electrical Engines. IEEE Trans. Vis. Comput. Graph. 28 (1) (2022)
Lun Ai, Johannes Langer, Stephen H. Muggleton, Ute Schmid
Explanatory machine learning for sequential human teaching. CoRR (2022)
Johannes Rabold, Michael Siebers, Ute Schmid
Generating contrastive explanations for inductive logic programming based on a near miss approach. Mach. Learn. 111 (5) (2022)
Marvin Herchenbach, Dennis Müller, Stephan Scheele, Ute Schmid
Explaining Image Classifications with Near Misses, Near Hits and Prototypes - Supporting Domain Experts in Understanding Decision Boundaries. ICPRAI (2) (2022)
Teena Hassan, Dominik Seuß, Johannes Wollenberg, Katharina Weitz, Miriam Kunz, Stefan Lautenbacher, Jens-Uwe Garbas, Ute Schmid
Automatic Detection of Pain from Facial Expressions: A Survey. IEEE Trans. Pattern Anal. Mach. Intell. 43 (6) (2021)
Andrew Cropper, Luc De Raedt, Richard Evans, Ute Schmid
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192). Dagstuhl Reports 11 (4) (2021)
Lun Ai, Stephen H. Muggleton, Céline Hocquette, Mark Gromowski, Ute Schmid
Beneficial and harmful explanatory machine learning. Mach. Learn. 110 (4) (2021)
Deniz Neufeld, Ute Schmid
Anomaly Detection for Hydraulic Systems under Test. ETFA (2021)
Johannes Rabold, Michael Siebers, Ute Schmid
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach. CoRR (2021)
Sascha Lang, Valentin Plenk, Ute Schmid
A Case-Based Reasoning Approach for a Decision Support System in Manufacturing. IEA/AIE (2) (2021)
Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid
Explanation as a process: user-centric construction of multi-level and multi-modal explanations. CoRR (2021)
Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid
Explanation as a Process: User-Centric Construction of Multi-level and Multi-modal Explanations. KI (2021)
Jonas-Dario Troles, Ute Schmid
Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives. WMT@EMNLP (2021)
Ute Schmid, Anja Gärtig-Daugs, Linda Müller, Alexander Werner
Grundkonzepte des Maschinellen Lernens für die Grundschule - Algorithmen, Biases, Generalisierungsfehler. GI-Jahrestagung (2021)
Anna Magdalena Thaler, Ute Schmid
Explaining Machine Learned Relational Concepts in Visual Domains - Effects of Perceived Accuracy on Joint Performance and Trust. CogSci (2021)
Johannes Rabold, Gesina Schwalbe, Ute Schmid
Expressive Explanations of DNNs by Combining Concept Analysis with ILP. CoRR (2021)
Bettina Finzel, René Kollmann, Ines Rieger, Jaspar Pahl, Ute Schmid
Deriving Temporal Prototypes from Saliency Map Clusters for the Analysis of Deep-Learning-based Facial Action Unit Classification. LWDA (2021)
Jonas-Dario Troles, Ute Schmid
Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives. CoRR (2021)
Bettina Finzel, David Elias Tafler, Anna Magdalena Thaler, Ute Schmid
Multimodal Explanations for User-centric Medical Decision Support Systems. HUMAN@AAAI Fall Symposium (2021)
Ute Schmid, Bettina Finzel
Mutual Explanations for Cooperative Decision Making in Medicine. Künstliche Intell. 34 (2) (2020)
Ines Rieger, Rene Kollmann, Bettina Finzel, Dominik Seuss, Ute Schmid
Verifying Deep Learning-based Decisions for Facial Expression Recognition. ESANN (2020)
Johannes Rabold, Gesina Schwalbe, Ute Schmid
Expressive Explanations of DNNs by Combining Concept Analysis with ILP. KI (2020)
Lun Ai, Stephen H. Muggleton, Céline Hocquette, Mark Gromowski, Ute Schmid
Beneficial and Harmful Explanatory Machine Learning. CoRR (2020)
Ute Schmid
AI goes to school: learning about and learning with artificial intelligence. WiPSCE (2020)
Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen
Künstliche Intelligenz - Die dritte Welle. GI-Jahrestagung (2020)
Mark Gromowski, Michael Siebers, Ute Schmid
A process framework for inducing and explaining Datalog theories. Adv. Data Anal. Classif. 14 (4) (2020)
Sebastian Bruckert, Bettina Finzel, Ute Schmid
The Next Generation of Medical Decision Support: A Roadmap Toward Transparent Expert Companions. Frontiers Artif. Intell. 3 (2020)
Ines Rieger, Rene Kollmann, Bettina Finzel, Dominik Seuss, Ute Schmid
Verifying Deep Learning-based Decisions for Facial Expression Recognition. CoRR (2020)
Luc De Raedt, Richard Evans, Stephen H. Muggleton, Ute Schmid
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 19202). Dagstuhl Reports 9 (5) (2019)
Johannes Rabold, Hannah Deininger, Michael Siebers, Ute Schmid
Enriching Visual with Verbal Explanations for Relational Concepts - Combining LIME with Aleph. CoRR (2019)
Anja Gärtig-Daugs, Alexander Werner, Ute Schmid
"Wie funktioniert das?" - Informatische Konzepte in der Vor- und Grundschule spielerisch begreifen und anwenden. INFOS (2019)
Johannes Rabold, Hannah Deininger, Michael Siebers, Ute Schmid
Enriching Visual with Verbal Explanations for Relational Concepts - Combining LIME with Aleph. PKDD/ECML Workshops (1) (2019)
Ludwig Schallner, Johannes Rabold, Oliver Scholz, Ute Schmid
Effect of Superpixel Aggregation on Explanations in LIME - A Case Study with Biological Data. CoRR (2019)
Michael Siebers, Ute Schmid
Please delete that! Why should I? - Explaining learned irrelevance classifications of digital objects. Künstliche Intell. 33 (1) (2019)
Ludwig Schallner, Johannes Rabold, Oliver Scholz, Ute Schmid
Effect of Superpixel Aggregation on Explanations in LIME - A Case Study with Biological Data. PKDD/ECML Workshops (1) (2019)
Michael Siebers, Ute Schmid
Was the Year 2000 a Leap Year? Step-Wise Narrowing Theories with Metagol. ILP (2018)
Stephen H. Muggleton, Ute Schmid, Christina Zeller, Alireza Tamaddoni-Nezhad, Tarek R. Besold
Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP. Mach. Learn. 107 (7) (2018)
Ute Schmid, Katharina Weitz, Anja Gärtig-Daugs
Informatik in der Grundschule - Eine informatisch-pädagogische Perspektive auf informatikdidaktische Konzepte. Inform. Spektrum 41 (3) (2018)
Bettina Finzel, Hannah Deininger, Ute Schmid
From beliefs to intention: mentoring as an approach to motivate female high school students to enrol in computer science studies. GenderIT (2018)
Ute Schmid
Inductive Programming as Approach to Comprehensible Machine Learning. DKB/KIK@KI (2018)
Johannes Rabold, Michael Siebers, Ute Schmid
Explaining Black-Box Classifiers with ILP - Empowering LIME with Aleph to Approximate Non-linear Decisions with Relational Rules. ILP (2018)
Ingo J. Timm, Steffen Staab, Michael Siebers, Claudia Schon, Ute Schmid, Kai Sauerwald, Lukas Reuter, Marco Ragni, Claudia Niederée, Heiko Maus, Gabriele Kern-Isberner, Christian Jilek, Paulina Friemann, Thomas Eiter, Andreas Dengel, Hannah Dames, Tanja Bock, Jan Ole Berndt, Christoph Beierle
Intentional Forgetting in Artificial Intelligence Systems: Perspectives and Challenges. KI (2018)
Maike Wolking, Ute Schmid
Mental Models, Career Aspirations, and the Acquirement of Basic Concepts of Computer Science in Elementary Education: Empirical Evaluation of the Computer Science Experimenter's Kit. WiPSCE (2017)
Ute Schmid, Stephen H. Muggleton, Rishabh Singh
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382). Dagstuhl Reports 7 (9) (2017)
Christina Zeller, Ute Schmid
The Impact of Presentation Order on Category Learning Strategies: Behavioral Data and Self-Reports. CogSci (2017)
Frederick Birnbaum, Christian Moewes, Daniela Nicklas, Ute Schmid
Data Mining von multidimensionalen Qualitätsdaten aus einer computerintegrierten industriellen Fertigung zur visuellen Analyse von komplexen Wirkzusammenhängen. BTW (Workshops) (2017)
Anja Gärtig-Daugs, Katharina Weitz, Ute Schmid
Kindliche Modelle der digitalen Welt. INFOS (2017)
Aboubakr Benabbas, Golnaz Elmamooz, Brent Lagesse, Daniela Nicklas, Ute Schmid
Living Lab Bamberg: an infrastructure to explore smart city research challenges in the wild. Künstliche Intell. 31 (3) (2017)
Christina Zeller, Ute Schmid
A Human Like Incremental Decision Tree Algorithm: Combining Rule Learning, Pattern Induction, and Storing Examples. LWDA (2017)
Katharina Weitz, Anja Gärtig-Daugs, Daniel Knauf, Ute Schmid
Computer Science in Early Childhood Education: Pedagogical Beliefs and Perceived Self-Confidence in Preschool Teachers. WiPSCE (2017)
Michael Siebers, Kyra Gobel, Cornelia Niessen, Ute Schmid
Requirements for a companion system to support identifying irrelevancy. ICCT (2017)
José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe
Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract). IJCAI (2017)
Teena Hassan, Dominik Seuss, Johannes Wollenberg, Jens-Uwe Garbas, Ute Schmid
A Practical Approach to Fuse Shape and Appearance Information in a Gaussian Facial Action Estimation Framework. ECAI (2016)
Ute Schmid, Christina Zeller, Tarek R. Besold, Alireza Tamaddoni-Nezhad, Stephen Muggleton
How Does Predicate Invention Affect Human Comprehensibility? ILP (2016)
José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe
Computer models solving intelligence test problems: Progress and implications. Artif. Intell. 230 (2016)
Christina Zeller, Ute Schmid
Automatic Generation of Analogous Problems to Help Resolving Misconceptions in an Intelligent Tutor System for Written Subtraction. ICCBR Workshops (2016)
Anja Gärtig-Daugs, Katharina Weitz, Maike Wolking, Ute Schmid
Computer science experimenter's kit for use in preschool and primary school. WiPSCE (2016)
Michael Siebers, Ute Schmid, Dominik Seuß, Miriam Kunz, Stefan Lautenbacher
Characterizing facial expressions by grammars of action unit sequences - A first investigation using ABL. Inf. Sci. 329 (2016)
Michael Siebers, Franz Uhrmann, Oliver Scholz, Christoph Stocker, Ute Schmid
Automatische Detektion von Trockenstress bei Tabakpflanzen mittels Machine-Learning-Verfahren. GIL Jahrestagung (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ute Schmid