Ute Schmid

228 papers A* 3A 3B 9C 5Misc 16Journal 96Unranked 60
YearRankTypeTitle / Venue / Authors
2026 A* conf
Can Humans Teach Machines to Code?
AAAI
Céline Hocquette, Johannes Langer, Andrew Cropper, Ute Schmid
2026 — ed.
Digital Humanism - First Interdisciplinary Science and Research Conference, DIGHUM 2025, Vienna, Austria, November 20-21, 2025, Proceedings
DIGHUM
Ludger Hagedorn, Ute Schmid, Susan J. Winter, Stefan Woltran
2026 — ed.
Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part I
xAI (1)
Riccardo Guidotti, Ute Schmid, Luca Longo
2026 — ed.
Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part II
xAI (2)
Riccardo Guidotti, Ute Schmid, Luca Longo
2026 — ed.
Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part III
xAI (3)
Riccardo Guidotti, Ute Schmid, Luca Longo
2026 — ed.
Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part IV
xAI (4)
Riccardo Guidotti, Ute Schmid, Luca Longo
2026 — ed.
Explainable Artificial Intelligence - Third World Conference, xAI 2025, Istanbul, Turkey, July 9-11, 2025, Proceedings, Part V
xAI (5)
Riccardo Guidotti, Ute Schmid, Luca Longo
2026 J jnl
The Dual Role of Abstracting over the Irrelevant in Symbolic Explanations: Cognitive Effort vs. Understanding.
CoRR
Zeynep G. Saribatur, Johannes Langer, Ute Schmid
2026 — ch.
Vertrauenswürdige Künstliche Intelligenz.
Künstliche Intelligenz und Wir: Stand, Nutzung und Herausforderungen der KI
Ute Schmid
2026 J jnl
Why do women pursue a Ph.D. in Computer Science?
J. Syst. Softw.
Erika Ábrahám, Miguel Goulão, Milena Vujosevic-Janicic, Sarah Jane Delany, Amal Mersni, Oleksandra Yeremenko, Ozge Buyukdagli, Karima Boudaoud, Caroline Oehlhorn, Ute Schmid, Christina Büsing, Helen Bolke-Hermanns, Kaja Köhnle, Matilde Pato, Deniz Sunar Cerci, Larissa Schmid
2025 — conf
Comparing Mask R-CNN and Mask2Former architectures for individual tree crown delineation.
GIL
Sonja Ruschhaupt, Jonas Troles, Ute Schmid
2025 — conf
Concepts Guide and Explain Diffusion Visual Counterfactuals.
xAI (Late-breaking Work, Demos, Doctoral Consortium)
Franz Motzkus, Ute Schmid
2025 — conf
Explaining Process Behavior: A Declarative Framework for Interpretable Event Data.
xAI (Late-breaking Work, Demos, Doctoral Consortium)
Christian Dormagen, Jonas Amling, Stephan Scheele, Ute Schmid
2025 J jnl
FMC-Net: A Human-Guided Deep Learning Framework for Adaptable and Transparent Facial Expression Recognition in Real-World Scenarios.
Appl. Intell.
Ines Rieger, Jaspar Pahl, Ute Schmid
2025 J jnl
Generative Large Language Models (gLLMs) in Content Analysis: A Practical Guide for Communication Research.
CoRR
Daria Kravets-Meinke, Hannah Schmid-Petri, Sonja Niemann, Ute Schmid
2025 J jnl
Knowledge graph enhanced retrieval-augmented generation for failure mode and effects analysis.
J. Ind. Inf. Integr.
Lukas Bahr, Christoph Wehner, Judith Wewerka, José Bittencourt, Ute Schmid, Rüdiger Daub
2025 — conf
Mehr Pionierinnen für die Informatik - Ein Programm zur Inspiration und Orientierung zum Informatikstudium für Schülerinnen.
INFOS
Nadine Dittert, Nils Pancratz, Ute Schmid, Claude Draude
2025 J jnl
OmniPlantSeg: Species Agnostic 3D Point Cloud Organ Segmentation for High-Resolution Plant Phenotyping Across Modalities.
CoRR
Andreas Gilson, Lukas Meyer, Oliver Scholz, Ute Schmid
2025 J jnl
Project VoLL-KI.
Künstliche Intell.
Michael Kohlhase, Marc Berges, Jens Grubert, Andreas Henrich, Dieter Landes, Jochen L. Leidner, Florian Mittag, Daniela Nicklas, Ute Schmid, Yvonne Sedlmaier, Achim Ulbrich-vom Ende, Diedrich Wolter
2025 Misc conf
Re-evaluating the Robustness and Interpretability of the Contrastive Explanations Method for Image Classification.
KI
Luisa Schneider, Bettina Finzel, Ute Schmid
2025 Misc conf
Toward Simple and Robust Contrastive Explanations for Image Classification by Leveraging Instance Similarity and Concept Relevance.
KI
Yuliia Kaidashova, Bettina Finzel, Ute Schmid
2025 J jnl
Toward Simple and Robust Contrastive Explanations for Image Classification by Leveraging Instance Similarity and Concept Relevance.
CoRR
Yuliia Kaidashova, Bettina Finzel, Ute Schmid
2025 Misc conf
Towards Observing the Effect of Abstraction on Understandability of Explanations in Answer Set Programming.
KI
Zeynep G. Saribatur, Johannes Langer, Anna Magdalena Thaler, Ute Schmid
2025 J jnl
USeR: A Web-based User Story eReviewer for Assisted Quality Optimizations.
CoRR
Daniel Hallmann, Kerstin Jacob, Gerald Lüttgen, Ute Schmid, Rüdiger von der Weth
2025 J jnl
Ultra Strong Machine Learning: Teaching Humans Active Learning Strategies via Automated AI Explanations.
CoRR
Lun Ai, Johannes Langer, Ute Schmid, Stephen H. Muggleton
2025 J jnl
Was alle über Künstliche Intelligenz wissen sollen und wie KI-bezogene Kompetenzen in der Schule entwickelt werden können.
Inform. Spektrum
Daniel Losch, Steffen Jaschke, Tilman Michaeli, Simone Opel, Ute Schmid, Stefan Seegerer, Peer Stechert
2025 J jnl
Why do women pursue a PhD in Computer Science?
CoRR
Erika Ábrahám, Miguel Goulão, Milena Vujosevic-Janicic, Sarah Jane Delany, Amal Mersni, Oleksandra Yeremenko, Ozge Buyukdagli, Karima Boudaoud, Caroline Oehlhorn, Ute Schmid, Christina Büsing, Helen Bolke-Hermanns, Kaja Köhnle, Matilde Pato, Deniz Sunar Cerci, Larissa Schmid
2025 Misc conf
XAIRob - An Explainable-AI-Based Relative Robustness Measure for Object Detection.
KI
Benedikt Schlereth-Groh, Ramin Tavakoli Kolagari, Ute Schmid
2024 J jnl
Aligning Generalisation Between Humans and Machines.
CoRR
Filip Ilievski, Barbara Hammer, Frank van Harmelen, Benjamin Paassen, Sascha Saralajew, Ute Schmid, Michael Biehl, Marianna Bolognesi, Xin Luna Dong, Kiril Gashteovski, Pascal Hitzler, Giuseppe Marra, Pasquale Minervini, Martin Mundt, Axel-Cyrille Ngonga Ngomo, Alessandro Oltramari, Gabriella Pasi, Zeynep G. Saribatur, Luciano Serafini, John Shawe-Taylor, Vered Shwartz, Gabriella Skitalinskaya, Clemens Stachl, Gido M. van de Ven, Thomas Villmann
2024 — ed.
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I
ECAI Workshops (1)
Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
2024 — ed.
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II
ECAI Workshops (2)
Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova
2024 J jnl
BAMFORESTS: Bamberg Benchmark Forest Dataset of Individual Tree Crowns in Very-High-Resolution UAV Images.
Remote. Sens.
Jonas Troles, Ute Schmid, Wen Fan, Jiaojiao Tian
2024 J jnl
Can humans teach machines to code?
CoRR
Céline Hocquette, Johannes Langer, Andrew Cropper, Ute Schmid
2024 — conf
CherryGraph: Encoding digital twins of cherry trees into a knowledge graph based on topology.
GIL
Andreas Gilson, Mareike Weule, Jonathan Hansen, Lukas Meyer, Fabian Keil, Oliver Scholz, Annika Killer, Patrick Noack, Marc Stamminger, Ute Schmid
2024 J jnl
CoLa-DCE - Concept-guided Latent Diffusion Counterfactual Explanations.
CoRR
Franz Motzkus, Christian Hellert, Ute Schmid
2024 J jnl
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey.
CoRR
Simon Schramm, Christoph Wehner, Ute Schmid
2024 — ch.
Einführung.
Künstliche Intelligenz für Lehrkräfte
Ulrich Furbach, Ute Schmid
2024 — ch.
Erklärbarkeit.
Künstliche Intelligenz für Lehrkräfte
Ute Schmid
2024 — conf
Explainable AI for Mixed Data Clustering.
xAI (2)
Jonas Amling, Stephan Scheele, Emanuel Slany, Moritz Lang, Ute Schmid
2024 J jnl
Explainable and interpretable machine learning and data mining.
Data Min. Knowl. Discov.
Martin Atzmueller, Johannes Fürnkranz, Tomás Kliegr, Ute Schmid
2024 Misc conf
Explanatory Interactive Machine Learning with Counterexamples from Constrained Large Language Models.
KI
Emanuel Slany, Stephan Scheele, Ute Schmid
2024 A conf
FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework.
IROS
Lukas Meyer, Andreas Gilson, Ute Schmid, Marc Stamminger
2024 J jnl
FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework.
CoRR
Lukas Meyer, Andreas Gilson, Ute Schmid, Marc Stamminger
2024 — ch.
Generative KI.
Künstliche Intelligenz für Lehrkräfte
Johannes Langer, Ute Schmid
2024 J jnl
Human-AI Collaboration in Coding: A Trust Perspective.
Electron. Commun. Eur. Assoc. Softw. Sci. Technol.
Sonja Niemann, Ute Schmid
2024 — conf
Hybrid Explanatory Interactive Machine Learning for Medical Diagnosis.
AIAI (1)
Emanuel Slany, Stephan Scheele, Ute Schmid
2024 — conf
Interactive Explainable Anomaly Detection for Industrial Settings.
ECCV Workshops (4)
Daniel Gramelt, Timon Höfer, Ute Schmid
2024 J jnl
Interactive Explainable Anomaly Detection for Industrial Settings.
CoRR
Daniel Gramelt, Timon Höfer, Ute Schmid
2024 J jnl
Knowledge Graph Enhanced Retrieval-Augmented Generation for Failure Mode and Effects Analysis.
CoRR
Lukas Bahr, Christoph Wehner, Judith Wewerka, José Bittencourt, Ute Schmid, Rüdiger Daub
2024 — book
Künstliche Intelligenz für Lehrkräfte: Eine fachliche Einführung mit didaktischen Hinweisen
Künstliche Intelligenz für Lehrkräfte
Ulrich Furbach, Emanuel Kitzelmann, Tilman Michaeli, Ute Schmid
2024 — conf
Locally Testing Model Detections for Semantic Global Concepts.
xAI (1)
Franz Motzkus, Georgii Mikriukov, Christian Hellert, Ute Schmid
2024 J jnl
Locally Testing Model Detections for Semantic Global Concepts.
CoRR
Franz Motzkus, Georgii Mikriukov, Christian Hellert, Ute Schmid
2024 — ch.
Natürliche und Künstliche Intelligenz.
Künstliche Intelligenz für Lehrkräfte
Ute Schmid
2024 — conf
Near Hit and Near Miss Example Explanations for Model Revision in Binary Image Classification.
IDEAL (2)
Bettina Finzel, Judith Knoblach, Anna Magdalena Thaler, Ute Schmid
2024 — conf
SPECTRE: A Dataset for Spectral Reconstruction on Chip-Size Spectrometers with a Physics-Informed Augmentation Method.
IEEE SENSORS
Julio Wissing, Teresa Scholz, Stefan Saloman, Lidia Fargueta, Stephan Junger, Alessio Stefani, Wladimir Tschekalinskij, Stephan Scheele, Ute Schmid
2024 — ch.
Suche im Problemraum.
Künstliche Intelligenz für Lehrkräfte
Ute Schmid
2024 J jnl
When a Relation Tells More Than a Concept: Exploring and Evaluating Classifier Decisions with CoReX.
CoRR
Bettina Finzel, Patrick Hilme, Johannes Rabold, Ute Schmid
2023 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 23442).
Dagstuhl Reports
Luc De Raedt, Ute Schmid, Johannes Langer
2023 — conf
Bayesian CAIPI: A Probabilistic Approach to Explanatory and Interactive Machine Learning.
ECAI Workshops (1)
Emanuel Slany, Stephan Scheele, Ute Schmid
2023 — conf
Cluster Robust Inference for Embedding-Based Knowledge Graph Completion.
KSEM (1)
Simon Schramm, Ulrich Niklas, Ute Schmid
2023 J jnl
Comprehensible Artificial Intelligence on Knowledge Graphs: A survey.
J. Web Semant.
Simon Schramm, Christoph Wehner, Ute Schmid
2023 C conf
Domain-Specific Evaluation of Visual Explanations for Application-Grounded Facial Expression Recognition.
CD-MAKE
Bettina Finzel, Ines Rieger, Simon Kuhn, Ute Schmid
2023 J jnl
Explaining Hate Speech Classification with Model Agnostic Methods.
CoRR
Durgesh Nandini, Ute Schmid
2023 J jnl
Explaining with Attribute-based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust.
CoRR
Bettina Finzel, Simon P. Kuhn, David E. Tafler, Ute Schmid
2023 J jnl
Explanatory machine learning for sequential human teaching.
Mach. Learn.
Lun Ai, Johannes Langer, Stephen H. Muggleton, Ute Schmid
2023 J jnl
FairCaipi: A Combination of Explanatory Interactive and Fair Machine Learning for Human and Machine Bias Reduction.
Mach. Learn. Knowl. Extr.
Louisa Heidrich, Emanuel Slany, Stephan Scheele, Ute Schmid
2023 — conf
Inductive Logic Programming for Explainable Graph Clustering.
ICKG
Simon Schramm, Ute Schmid
2023 J jnl
ManuKnowVis: How to Support Different User Groups in Contextualizing and Leveraging Knowledge Repositories.
IEEE Trans. Vis. Comput. Graph.
Joscha Eirich, Dominik Jäckle, Michael Sedlmair, Christoph Wehner, Ute Schmid, Jürgen Bernard, Tobias Schreck
2023 — conf
Perzeptrons programmieren und explorieren im Rahmen der Open Roberta Lernumgebung.
INFOS
Alisa Véronique Münsterberg, Reinhard Budde, Ute Schmid, Thorsten Leimbach
2023 C conf
Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data.
I4CS
Jonas Troles, Richard Nieding, Sonia Simons, Ute Schmid
2023 J jnl
Task Planning Support for Arborists and Foresters: Comparing Deep Learning Approaches for Tree Inventory and Tree Vitality Assessment Based on UAV-Data.
CoRR
Jonas-Dario Troles, Richard Nieding, Sonia Simons, Ute Schmid
2023 J jnl
Toward human-level concept learning: Pattern benchmarking for AI algorithms.
Patterns
Andreas Holzinger, Anna Saranti, Alessa Angerschmid, Bettina Finzel, Ute Schmid, Heimo Müller
2022 — conf
A Video-based Study on Perceived Intelligence, Subjective Performance and Trust under Variation of Prior Information given to Users in Autonomous Driving.
ARSO
Kolja Kühnlenz, Ute Schmid, Barbara Kühnlenz
2022 A* conf
An Interactive Explanatory AI System for Industrial Quality Control.
AAAI
Dennis Müller, Michael März, Stephan Scheele, Ute Schmid
2022 J jnl
An Interactive Explanatory AI System for Industrial Quality Control.
CoRR
Dennis Müller, Michael März, Stephan Scheele, Ute Schmid
2022 — conf
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification.
AIAI (Workshops)
Emanuel Slany, Yannik Ott, Stephan Scheele, Jan Paulus, Ute Schmid
2022 J jnl
CAIPI in Practice: Towards Explainable Interactive Medical Image Classification.
CoRR
Emanuel Slany, Yannik Ott, Stephan Scheele, Jan Paulus, Ute Schmid
2022 J jnl
Concept Embeddings for Fuzzy Logic Verification of Deep Neural Networks in Perception Tasks.
CoRR
Gesina Schwalbe, Christian Wirth, Ute Schmid
2022 J jnl
Constructing Explainability - Interdisciplinary Framework to Actively Shape Explanations in XAI.
Künstliche Intell.
Ute Schmid
2022 B conf
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition.
ICPR
Ines Rieger, Jaspar Pahl, Bettina Finzel, Ute Schmid
2022 J jnl
CorrLoss: Integrating Co-Occurrence Domain Knowledge for Affect Recognition.
CoRR
Ines Rieger, Jaspar Pahl, Bettina Finzel, Ute Schmid
2022 J jnl
Explainable AI.
Künstliche Intell.
Ute Schmid, Britta Wrede
2022 C conf
Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation.
IEA/AIE
Christoph Wehner, Francis Powlesland, Bashar Altakrouri, Ute Schmid
2022 J jnl
Explainable Online Lane Change Predictions on a Digital Twin with a Layer Normalized LSTM and Layer-wise Relevance Propagation.
CoRR
Christoph Wehner, Francis Powlesland, Bashar Altakrouri, Ute Schmid
2022 — conf
Explaining Hate Speech Classification with Model-Agnostic Methods.
KI (Workshops)
Durgesh Nandini, Ute Schmid
2022 — conf
Explaining Image Classifications with Near Misses, Near Hits and Prototypes - Supporting Domain Experts in Understanding Decision Boundaries.
ICPRAI (2)
Marvin Herchenbach, Dennis Müller, Stephan Scheele, Ute Schmid
2022 B conf
Explaining with Attribute-Based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust.
ILP
Bettina Finzel, Simon P. Kuhn, David E. Tafler, Ute Schmid
2022 J jnl
Explanatory machine learning for justified trust in human-AI collaboration: Experiments on file deletion recommendations.
Frontiers Artif. Intell.
Kyra Gobel, Cornelia Niessen, Sebastian Seufert, Ute Schmid
2022 J jnl
Explanatory machine learning for sequential human teaching.
CoRR
Lun Ai, Johannes Langer, Stephen H. Muggleton, Ute Schmid
2022 — conf
Female, white, 27? Bias Evaluation on Data and Algorithms for Affect Recognition in Faces.
FAccT
Jaspar Pahl, Ines Rieger, Anna Möller, Thomas Wittenberg, Ute Schmid
2022 J jnl
Generating contrastive explanations for inductive logic programming based on a near miss approach.
Mach. Learn.
Johannes Rabold, Michael Siebers, Ute Schmid
2022 — conf
HiMLEdge - Energy-Aware Optimization for Hierarchical Machine Learning.
ARTIIS (2)
Julio Wissing, Stephan Scheele, Aliya Mohammed, Dorothea Kolossa, Ute Schmid
2022 J jnl
IRVINE: A Design Study on Analyzing Correlation Patterns of Electrical Engines.
IEEE Trans. Vis. Comput. Graph.
Joscha Eirich, Jakob Bonart, Dominik Jäckle, Michael Sedlmair, Ute Schmid, Kai Fischbach, Tobias Schreck, Jürgen Bernard
2022 — ch.
Interactive Learning with Mutual Explanations in Relational Domains.
Human-Like Machine Intelligence
Ute Schmid
2022 J jnl
Semantic Interactive Learning for Text Classification: A Constructive Approach for Contextual Interactions.
Mach. Learn. Knowl. Extr.
Sebastian Kiefer, Mareike Hoffmann, Ute Schmid
2022 J jnl
What is Missing in XAI So Far?
Künstliche Intell.
Ute Schmid, Britta Wrede
2021 — conf
A Case-Based Reasoning Approach for a Decision Support System in Manufacturing.
IEA/AIE (2)
Sascha Lang, Valentin Plenk, Ute Schmid
2021 C conf
Anomaly Detection for Hydraulic Systems under Test.
ETFA
Deniz Neufeld, Ute Schmid
2021 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 21192).
Dagstuhl Reports
Andrew Cropper, Luc De Raedt, Richard Evans, Ute Schmid
2021 J jnl
Automatic Detection of Pain from Facial Expressions: A Survey.
IEEE Trans. Pattern Anal. Mach. Intell.
Teena Hassan, Dominik Seuß, Johannes Wollenberg, Katharina Weitz, Miriam Kunz, Stefan Lautenbacher, Jens-Uwe Garbas, Ute Schmid
2021 J jnl
Beneficial and harmful explanatory machine learning.
Mach. Learn.
Lun Ai, Stephen H. Muggleton, Céline Hocquette, Mark Gromowski, Ute Schmid
2021 — conf
Deriving Temporal Prototypes from Saliency Map Clusters for the Analysis of Deep-Learning-based Facial Action Unit Classification.
LWDA
Bettina Finzel, René Kollmann, Ines Rieger, Jaspar Pahl, Ute Schmid
2021 B conf
Explaining Machine Learned Relational Concepts in Visual Domains - Effects of Perceived Accuracy on Joint Performance and Trust.
CogSci
Anna Magdalena Thaler, Ute Schmid
2021 Misc conf
Explanation as a Process: User-Centric Construction of Multi-level and Multi-modal Explanations.
KI
Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid
2021 J jnl
Explanation as a process: user-centric construction of multi-level and multi-modal explanations.
CoRR
Bettina Finzel, David E. Tafler, Stephan Scheele, Ute Schmid
2021 J jnl
Expressive Explanations of DNNs by Combining Concept Analysis with ILP.
CoRR
Johannes Rabold, Gesina Schwalbe, Ute Schmid
2021 — conf
Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives.
WMT@EMNLP
Jonas-Dario Troles, Ute Schmid
2021 J jnl
Extending Challenge Sets to Uncover Gender Bias in Machine Translation: Impact of Stereotypical Verbs and Adjectives.
CoRR
Jonas-Dario Troles, Ute Schmid
2021 J jnl
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach.
CoRR
Johannes Rabold, Michael Siebers, Ute Schmid
2021 — conf
Grundkonzepte des Maschinellen Lernens für die Grundschule - Algorithmen, Biases, Generalisierungsfehler.
GI-Jahrestagung
Ute Schmid, Anja Gärtig-Daugs, Linda Müller, Alexander Werner
2021 — conf
Multimodal Explanations for User-centric Medical Decision Support Systems.
HUMAN@AAAI Fall Symposium
Bettina Finzel, David Elias Tafler, Anna Magdalena Thaler, Ute Schmid
2021 — ed.
Proceedings of the First International Workshop on Explainable and Interpretable Machine Learning (XI-ML 2020) co-located with the 43rd German Conference on Artificial Intelligence (KI 2020), Bamberg, Germany, September 21, 2020 (Virtual Workshop).
XI-ML@KI
Martin Atzmüller, Tomás Kliegr, Ute Schmid
2020 J jnl
A process framework for inducing and explaining Datalog theories.
Adv. Data Anal. Classif.
Mark Gromowski, Michael Siebers, Ute Schmid
2020 — conf
AI goes to school: learning about and learning with artificial intelligence.
WiPSCE
Ute Schmid
2020 J jnl
Beneficial and Harmful Explanatory Machine Learning.
CoRR
Lun Ai, Stephen H. Muggleton, Céline Hocquette, Mark Gromowski, Ute Schmid
2020 — ch.
Einleitung.
Handbuch der Künstlichen Intelligenz
Günther Görz, Tanya Braun, Ute Schmid
2020 Misc conf
Expressive Explanations of DNNs by Combining Concept Analysis with ILP.
KI
Johannes Rabold, Gesina Schwalbe, Ute Schmid
2020 — book
Handbuch der Künstlichen Intelligenz, 6. Auflage
Günther Görz, Ute Schmid, Tanya Braun
2020 Misc ed.
KI 2020: Advances in Artificial Intelligence - 43rd German Conference on AI, Bamberg, Germany, September 21-25, 2020, Proceedings
KI
Ute Schmid, Franziska Klügl, Diedrich Wolter
2020 — conf
Künstliche Intelligenz - Die dritte Welle.
GI-Jahrestagung
Ute Schmid, Volker Tresp, Matthias Bethge, Kristian Kersting, Rainer Stiefelhagen
2020 J jnl
Mutual Explanations for Cooperative Decision Making in Medicine.
Künstliche Intell.
Ute Schmid, Bettina Finzel
2020 J jnl
The Next Generation of Medical Decision Support: A Roadmap Toward Transparent Expert Companions.
Frontiers Artif. Intell.
Sebastian Bruckert, Bettina Finzel, Ute Schmid
2020 B conf
Verifying Deep Learning-based Decisions for Facial Expression Recognition.
ESANN
Ines Rieger, Rene Kollmann, Bettina Finzel, Dominik Seuss, Ute Schmid
2020 J jnl
Verifying Deep Learning-based Decisions for Facial Expression Recognition.
CoRR
Ines Rieger, Rene Kollmann, Bettina Finzel, Dominik Seuss, Ute Schmid
2019 — conf
"Wie funktioniert das?" - Informatische Konzepte in der Vor- und Grundschule spielerisch begreifen und anwenden.
INFOS
Anja Gärtig-Daugs, Alexander Werner, Ute Schmid
2019 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 19202).
Dagstuhl Reports
Luc De Raedt, Richard Evans, Stephen H. Muggleton, Ute Schmid
2019 — conf
Effect of Superpixel Aggregation on Explanations in LIME - A Case Study with Biological Data.
PKDD/ECML Workshops (1)
Ludwig Schallner, Johannes Rabold, Oliver Scholz, Ute Schmid
2019 J jnl
Effect of Superpixel Aggregation on Explanations in LIME - A Case Study with Biological Data.
CoRR
Ludwig Schallner, Johannes Rabold, Oliver Scholz, Ute Schmid
2019 — conf
Enriching Visual with Verbal Explanations for Relational Concepts - Combining LIME with Aleph.
PKDD/ECML Workshops (1)
Johannes Rabold, Hannah Deininger, Michael Siebers, Ute Schmid
2019 J jnl
Enriching Visual with Verbal Explanations for Relational Concepts - Combining LIME with Aleph.
CoRR
Johannes Rabold, Hannah Deininger, Michael Siebers, Ute Schmid
2019 J jnl
Please delete that! Why should I? - Explaining learned irrelevance classifications of digital objects.
Künstliche Intell.
Michael Siebers, Ute Schmid
2018 B conf
Explaining Black-Box Classifiers with ILP - Empowering LIME with Aleph to Approximate Non-linear Decisions with Relational Rules.
ILP
Johannes Rabold, Michael Siebers, Ute Schmid
2018 — conf
From beliefs to intention: mentoring as an approach to motivate female high school students to enrol in computer science studies.
GenderIT
Bettina Finzel, Hannah Deininger, Ute Schmid
2018 — conf
Inductive Programming as Approach to Comprehensible Machine Learning.
DKB/KIK@KI
Ute Schmid
2018 J jnl
Informatik in der Grundschule - Eine informatisch-pädagogische Perspektive auf informatikdidaktische Konzepte.
Inform. Spektrum
Ute Schmid, Katharina Weitz, Anja Gärtig-Daugs
2018 Misc conf
Intentional Forgetting in Artificial Intelligence Systems: Perspectives and Challenges.
KI
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
2018 J jnl
Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP.
Mach. Learn.
Stephen H. Muggleton, Ute Schmid, Christina Zeller, Alireza Tamaddoni-Nezhad, Tarek R. Besold
2018 B conf
Was the Year 2000 a Leap Year? Step-Wise Narrowing Theories with Metagol.
ILP
Michael Siebers, Ute Schmid
2017 — conf
A Human Like Incremental Decision Tree Algorithm: Combining Rule Learning, Pattern Induction, and Storing Examples.
LWDA
Christina Zeller, Ute Schmid
2017 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 17382).
Dagstuhl Reports
Ute Schmid, Stephen H. Muggleton, Rishabh Singh
2017 A* conf
Computer Models Solving Intelligence Test Problems: Progress and Implications (Extended Abstract).
IJCAI
José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe
2017 — conf
Computer Science in Early Childhood Education: Pedagogical Beliefs and Perceived Self-Confidence in Preschool Teachers.
WiPSCE
Katharina Weitz, Anja Gärtig-Daugs, Daniel Knauf, Ute Schmid
2017 — conf
Data Mining von multidimensionalen Qualitätsdaten aus einer computerintegrierten industriellen Fertigung zur visuellen Analyse von komplexen Wirkzusammenhängen.
BTW (Workshops)
Frederick Birnbaum, Christian Moewes, Daniela Nicklas, Ute Schmid
2017 — ch.
Inductive Programming.
Encyclopedia of Machine Learning and Data Mining
Pierre Flener, Ute Schmid
2017 — conf
Kindliche Modelle der digitalen Welt.
INFOS
Anja Gärtig-Daugs, Katharina Weitz, Ute Schmid
2017 J jnl
Living Lab Bamberg: an infrastructure to explore smart city research challenges in the wild.
Künstliche Intell.
Aboubakr Benabbas, Golnaz Elmamooz, Brent Lagesse, Daniela Nicklas, Ute Schmid
2017 — conf
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
Maike Wolking, Ute Schmid
2017 — ch.
Programming by Demonstration.
Encyclopedia of Machine Learning and Data Mining
Pierre Flener, Ute Schmid
2017 — conf
Requirements for a companion system to support identifying irrelevancy.
ICCT
Michael Siebers, Kyra Gobel, Cornelia Niessen, Ute Schmid
2017 B conf
The Impact of Presentation Order on Category Learning Strategies: Behavioral Data and Self-Reports.
CogSci
Christina Zeller, Ute Schmid
2017 — ch.
Trace-Based Programming.
Encyclopedia of Machine Learning and Data Mining
Pierre Flener, Ute Schmid
2016 A conf
A Practical Approach to Fuse Shape and Appearance Information in a Gaussian Facial Action Estimation Framework.
ECAI
Teena Hassan, Dominik Seuss, Johannes Wollenberg, Jens-Uwe Garbas, Ute Schmid
2016 — conf
Automatic Generation of Analogous Problems to Help Resolving Misconceptions in an Intelligent Tutor System for Written Subtraction.
ICCBR Workshops
Christina Zeller, Ute Schmid
2016 — conf
Automatische Detektion von Trockenstress bei Tabakpflanzen mittels Machine-Learning-Verfahren.
GIL Jahrestagung
Michael Siebers, Franz Uhrmann, Oliver Scholz, Christoph Stocker, Ute Schmid
2016 J jnl
Characterizing facial expressions by grammars of action unit sequences - A first investigation using ABL.
Inf. Sci.
Michael Siebers, Ute Schmid, Dominik Seuß, Miriam Kunz, Stefan Lautenbacher
2016 J jnl
Computer models solving intelligence test problems: Progress and implications.
Artif. Intell.
José Hernández-Orallo, Fernando Martínez-Plumed, Ute Schmid, Michael Siebers, David L. Dowe
2016 — conf
Computer science experimenter's kit for use in preschool and primary school.
WiPSCE
Anja Gärtig-Daugs, Katharina Weitz, Maike Wolking, Ute Schmid
2016 — conf
Gemeinsame mentale Modelle in der agilen Softwareentwicklung: Ein Ansatz zur Erstellung von Gestaltungsempfehlungen für "gute" erfahrungsspezifische User Stories.
GI-Jahrestagung
Daniel Hallmann, Ute Schmid, Rüdiger von der Weth
2016 B conf
How Does Predicate Invention Affect Human Comprehensibility?
ILP
Ute Schmid, Christina Zeller, Tarek R. Besold, Alireza Tamaddoni-Nezhad, Stephen H. Muggleton
2015 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 15442).
Dagstuhl Reports
José Hernández-Orallo, Stephen H. Muggleton, Ute Schmid, Benjamin G. Zorn
2015 J jnl
Can Machine Intelligence be Measured in the Same Way as Human intelligence?
Künstliche Intell.
Tarek R. Besold, José Hernández-Orallo, Ute Schmid
2015 — conf
Cognitive Systems: Goals, Approaches, Applications.
GI-Jahrestagung
Ute Schmid
2015 — conf
Comparing Computer Models Solving Number Series Problems.
AGI
Ute Schmid, Marco Ragni
2015 J jnl
Inductive programming meets the real world.
Commun. ACM
Sumit Gulwani, José Hernández-Orallo, Emanuel Kitzelmann, Stephen H. Muggleton, Ute Schmid, Benjamin G. Zorn
2015 J jnl
Introvertierte Studenten, fleißige Studentinnen? - Geschlechtsspezifische Unterschiede in Motivation, Zufriedenheit und Wahrnehmungsmustern bei Informatikstudierenden - Ergebnisse aus Erstsemesterbefragungen an der Fakultät Wirtschaftsinformatik und Angewandte Informatik der Otto-Friedrich-Universität Bamberg differenziert nach Geschlecht.
Inform. Spektrum
Ute Schmid, Anja Gärtig-Daugs, Silvia Förtsch
2015 J jnl
You Need the AI Community - and the AI Community Needs You!
Künstliche Intell.
Ute Schmid
2014 Misc conf
Applying Inductive Program Synthesis to Induction of Number Series A Case Study with IGOR2.
KI
Jacqueline Hofmann, Emanuel Kitzelmann, Ute Schmid
2014 J jnl
Does AI Need a New Debate on Ethics?
Künstliche Intell.
Ute Schmid
2014 J jnl
Grounding Hierarchical Reinforcement Learning Models for Knowledge Transfer.
CoRR
Mark Wernsdorfer, Ute Schmid
2014 — ch.
How Similar is What I Get to What I Want: Matchmaking for Mobility Support.
Computational Approaches to Analogical Reasoning
Ute Schmid, Lukas Berle, Michael Munz, Klaus Stein, Martin Sticht
2013 J jnl
A cognitive model for predicting esthetical judgements as similarity to dynamic prototypes.
Cogn. Syst. Res.
Ute Schmid, Michael Siebers, Johannes Folger, Simone Schineller, Dominik Seuß, Marius Raab, Claus-Christian Carbon, Stella J. Faerber
2013 — conf
A machine learning approach to drought stress level classification of tobacco plants.
LWA
Christoph Stocker, Franz Uhrmann, Oliver Scholz, Michael Siebers, Ute Schmid
2013 J jnl
Approaches and Applications of Inductive Programming (Dagstuhl Seminar 13502).
Dagstuhl Reports
Sumit Gulwani, Emanuel Kitzelmann, Ute Schmid
2013 J jnl
Assistive Technology to Support the Mobility of Senior Citizens - Overcoming Mobility Barriers and Establishing Mobility Chains by Social Collaboration.
Künstliche Intell.
Christoph Schlieder, Ute Schmid, Michael Munz, Klaus Stein
2013 — ch.
Einleitung.
Handbuch der Künstlichen Intelligenz
Günther Görz, Ute Schmid, Ipke Wachsmuth
2013 — conf
Erkennung von Sequenzen mimischer Schmerzausdrücke durch genetische Programmierung.
LWA
Christoph Stocker, Michael Siebers, Ute Schmid
2013 — ch.
From Streams of Observations to Knowledge-Level Productive Predictions.
Human Behavior Recognition Technologies
Mark Wernsdorfer, Ute Schmid
2013 — book
Handbuch der Künstlichen Intelligenz, 5. Auflage
Günther Görz, Josef Schneeberger, Ute Schmid
2012 B conf
Analogical Problem Solving: Insights from Verbal Reports.
CogSci
Linn Gralla, Thora Tenbrink, Michael Siebers, Ute Schmid
2012 — conf
Applying Grammar Inference To Identify Generalized Patterns of Facial Expressions of Pain.
ICGI
Ute Schmid, Michael Siebers, Dominik Seuß, Miriam Kunz, Stefan Lautenbacher
2012 J jnl
KI und Informatik.
Künstliche Intell.
Ute Schmid
2012 Misc conf
Semi-analytic Natural Number Series Induction.
KI
Michael Siebers, Ute Schmid
2011 — conf
From Sensorimotor Graphs to Rules: An Agent Learns from a Stream of Experience.
AGI
Marius Raab, Mark Wernsdorfer, Emanuel Kitzelmann, Ute Schmid
2011 J jnl
Inductive rule learning on the knowledge level.
Cogn. Syst. Res.
Ute Schmid, Emanuel Kitzelmann
2011 — ed.
Proceedings of AAIP 2011 - 4th International Workshop on Approaches and Applications of Inductive Programming, Odense, Denmark, July 19, 2011
AAIP
Emanuel Kitzelmann, Ute Schmid
2011 J jnl
The challenge of complexity for cognitive systems.
Cogn. Syst. Res.
Ute Schmid, Marco Ragni, Cleotilde Gonzalez, Joachim Funke
2010 — ed.
Approaches and Applications of Inductive Programming, Third International Workshop, AAIP 2009, Edinburgh, UK, September 4, 2009. Revised Papers
AAIP
Ute Schmid, Emanuel Kitzelmann, Rinus Plasmeijer
2010 A conf
Data-Driven Detection of Recursive Program Schemes.
ECAI
Martin Hofmann, Ute Schmid
2010 — conf
Incident Mining Using Structural Prototypes.
IEA/AIE (2)
Ute Schmid, Martin Hofmann, Florian Bader, Tilmann Häberle, Thomas Schneider
2010 — ch.
Inductive Programming.
Encyclopedia of Machine Learning
Pierre Flener, Ute Schmid
2010 — conf
Interleaving Forward Backward Feature Selection.
KDIR
Michael Siebers, Ute Schmid
2010 — ch.
Programming by Demonstration.
Encyclopedia of Machine Learning
Pierre Flener, Ute Schmid
2010 — ch.
Trace-Based Programming.
Encyclopedia of Machine Learning
Pierre Flener, Ute Schmid
2010 — conf
Tracking von Gesichtsmimik mit Hilfe von Gitterstrukturen zur Klassifikation von schmerzrelevanten Action Units.
Bildverarbeitung für die Medizin
Christine Barthold, Anton Papst, Thomas Wittenberg, Christian Küblbeck, Stefan Lautenbacher, Ute Schmid, Sven Friedl
2009 J jnl
Editorial 3-2009.
Künstliche Intell.
Ute Schmid
2009 C conf
Evolutionary Programming Guided by Analytically Generated Seeds.
IJCCI
Neil Crossley, Emanuel Kitzelmann, Martin Hofmann, Ute Schmid
2009 J jnl
Inductive Programming.
Künstliche Intell.
Ute Schmid, Martin Hofmann, Emanuel Kitzelmann
2009 — conf
Porting IgorII from Maude to Haskell.
AAIP
Martin Hofmann, Emanuel Kitzelmann, Ute Schmid
2008 J jnl
An introduction to inductive programming.
Artif. Intell. Rev.
Pierre Flener, Ute Schmid
2008 Misc conf
Analysis and Evaluation of Inductive Programming Systems in a Higher-Order Framework.
KI
Martin Hofmann, Emanuel Kitzelmann, Ute Schmid
2008 — book
Classifier Learning for Imbalanced Data - a Comparison of kNN, SVM, and Decision Tree Learning.
Jörg Mennicke, Christian Münzenmayer, Ute Schmid
2008 J jnl
Cognition and AI.
Künstliche Intell.
Ute Schmid
2008 J jnl
Editorial.
Künstliche Intell.
Ute Schmid
2008 J jnl
Gasteditorial KI und Kognition.
Künstliche Intell.
Ute Schmid
2008 J jnl
Interview with Ken Forbus.
Künstliche Intell.
Ute Schmid
2008 J jnl
KI und Kognition - Service.
Künstliche Intell.
Ute Schmid
2008 J jnl
KogWis 2008.
Künstliche Intell.
Ute Schmid
2007 Misc conf
Inductive Synthesis of Recursive Functional Programs.
KI
Martin Hofmann, Andreas Hirschberger, Emanuel Kitzelmann, Ute Schmid
2007 — ed.
Proceedings of the Workshop on Approaches and Applications of Inductive Programming, AAIP'07, September 17, 2007, Warsaw, Poland
AAIP
Emanuel Kitzelmann, Ute Schmid
2007 J jnl
Transformational and derivational strategies in analogical problem solving.
Cogn. Process.
Sven-Eric Schelhorn, Jacqueline Griego, Ute Schmid
2006 — conf
Inducing Constructor Systems from Example-Terms by Detecting Syntactical Regularities.
RULE@FLoC
Emanuel Kitzelmann, Ute Schmid
2006 J jnl
Inductive Synthesis of Functional Programs: An Explanation Based Generalization Approach.
J. Mach. Learn. Res.
Emanuel Kitzelmann, Ute Schmid
2006 J jnl
Metaphors and heuristic-driven theory projection (HDTP).
Theor. Comput. Sci.
Helmar Gust, Kai-Uwe Kühnberger, Ute Schmid
2006 Misc conf
Solving Proportional Analogies by
KI
Stephan Weller, Ute Schmid
2005 — conf
An Explanation Based Generalization Approach to Inductive Synthesis of Functional Programs.
AAIP
Emanuel Kitzelmann, Ute Schmid
2005 — ed.
Workshop on Approaches and Applications of Inductive Programming, AAIP 2005, to be held in conjunction with the 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, August 7, 2005.
AAIP
Emanuel Kitzelmann, Roland Olsson, Ute Schmid
2004 — conf
Ontological Aspects of Computing Analogies.
ICCM
Helmar Gust, Kai-Uwe Kühnberger, Ute Schmid
2003 — book
Inductive Synthesis of Functional Programs, Universal Planning, Folding of Finite Programs, and Schema Abstraction by Analogical Reasoning
Ute Schmid
2003 J jnl
Inductive Synthesis of Functional Programs.
Künstliche Intell.
Ute Schmid
2002 Misc conf
Inductive Synthesis of Functional Programs.
AISC
Emanuel Kitzelmann, Ute Schmid, Martin Mühlpfordt, Fritz Wysotzki
2002 Misc conf
Integrating Function Application in State-Based Planning.
KI
Ute Schmid, Marina Müller, Fritz Wysotzki
2002 J jnl
Mitteilungen der Gesellschaft fuer Kognitionswissenschaft e.V.
Kognitionswissenschaft
Ute Schmid
2000 — conf
Applying Inductive Program Synthesis to Macro Learning.
AIPS
Ute Schmid, Fritz Wysotzki
2000 — conf
Inference and Visualization of Spatial Relations.
Spatial Cognition
Sylvia Wiebrock, Lars Wittenburg, Ute Schmid, Fritz Wysotzki
1998 — conf
Induction of Recursive Program Schemes.
ECML
Ute Schmid, Fritz Wysotzki
1998 — conf
Reference Frames for Spatial Inference in Text Understanding.
Spatial Cognition
Berry Claus, Klaus Eyferth, Carsten Gips, Robin Hörnig, Ute Schmid, Sylvia Wiebrock, Fritz Wysotzki
1997 J jnl
Programmieren durch analoges Schließen .
Kognitionswissenschaft
Ute Schmid
1994 — —
Erwerb rekursiver Programmiertechniken als Induktion von Konzepten und Regeln - ein kognitionswissenschaftlicher Zugang zum Erwerb kognitiver Fertigkeiten.
Ute Schmid