| Causal discovery with attention-based convolutional neural networks M Nauta, D Bucur, C Seifert Machine Learning and Knowledge Extraction 1 (1), 19, 2019 | 201 | 2019 |
| Neural prototype trees for interpretable fine-grained image recognition M Nauta, R Van Bree, C Seifert Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 198 | 2021 |
| On the beauty and usability of tag clouds C Seifert, B Kump, W Kienreich, G Granitzer, M Granitzer 2008 12th International Conference Information Visualisation, 17-25, 2008 | 178 | 2008 |
| From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI M Nauta, J Trienes, S Pathak, E Nguyen, M Peters, Y Schmitt, ... ACM Computing Surveys, 2023 | 172 | 2023 |
| A mobile vision system for urban detection with informative local descriptors G Fritz, C Seifert, L Paletta Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 30-30, 2006 | 137 | 2006 |
| How model accuracy and explanation fidelity influence user trust A Papenmeier, G Englebienne, C Seifert arXiv preprint arXiv:1907.12652, 2019 | 118 | 2019 |
| Robust and collective entity disambiguation through semantic embeddings S Zwicklbauer, C Seifert, M Granitzer Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 115 | 2016 |
| Biomedical text mining: state-of-the-art, open problems and future challenges A Holzinger, J Schantl, M Schroettner, C Seifert, K Verspoor Interactive Knowledge Discovery and Data Mining in Biomedical Informatics …, 2014 | 104 | 2014 |
| Window detection in facades H Ali, C Seifert, N Jindal, L Paletta, G Paar 14th International Conference on Image Analysis and Processing (ICIAP 2007 …, 2007 | 95 | 2007 |
| Visualizations of deep neural networks in computer vision: A survey C Seifert, A Aamir, A Balagopalan, D Jain, A Sharma, S Grottel, ... Transparent data mining for big and small data, 123-144, 2017 | 94 | 2017 |
| Q-learning of sequential attention for visual object recognition from informative local descriptors L Paletta, G Fritz, C Seifert Proceedings of the 22nd international conference on Machine learning, 649-656, 2005 | 77 | 2005 |
| Doser-a knowledge-base-agnostic framework for entity disambiguation using semantic embeddings S Zwicklbauer, C Seifert, M Granitzer The Semantic Web. Latest Advances and New Domains: 13th International …, 2016 | 70 | 2016 |
| Automated retrieval of att&ck tactics and techniques for cyber threat reports V Legoy, M Caselli, C Seifert, A Peter arXiv preprint arXiv:2004.14322, 2020 | 57 | 2020 |
| User-based active learning C Seifert, M Granitzer 2010 IEEE International Conference on Data Mining Workshops, 418-425, 2010 | 57 | 2010 |
| This looks like that, because... explaining prototypes for interpretable image recognition M Nauta, A Jutte, J Provoost, C Seifert Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 55 | 2021 |
| Uncovering and correcting shortcut learning in machine learning models for skin cancer diagnosis M Nauta, R Walsh, A Dubowski, C Seifert Diagnostics 12 (1), 40, 2021 | 47 | 2021 |
| Linked Data Query Wizard: A Novel Interface for Accessing SPARQL Endpoints. P Hoefler, M Granitzer, EE Veas, C Seifert LDOW, 2014 | 47 | 2014 |
| Seeing what the system thinks you know: visualizing evidence in an open learner model B Kump, C Seifert, G Beham, SN Lindstaedt, T Ley Proceedings of the 2nd international conference on learning analytics and …, 2012 | 47 | 2012 |
| STQS: Interpretable multi-modal Spatial-Temporal-seQuential model for automatic Sleep scoring S Pathak, C Lu, SB Nagaraj, M van Putten, C Seifert Artificial intelligence in medicine 114, 102038, 2021 | 46 | 2021 |
| It’s complicated: The relationship between user trust, model accuracy and explanations in ai A Papenmeier, D Kern, G Englebienne, C Seifert ACM Transactions on Computer-Human Interaction (TOCHI) 29 (4), 1-33, 2022 | 44 | 2022 |
Granitzer MichaelProfessor Computer Science, University PassauVerified email at uni-passau.de
