| explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning T Spinner, U Schlegel, H Schäfer, M El-Assady IEEE transactions on visualization and computer graphics 26 (1), 1064-1074, 2019 | 277 | 2019 |
| Towards a rigorous evaluation of XAI methods on time series U Schlegel, H Arnout, M El-Assady, D Oelke, DA Keim 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW …, 2019 | 159 | 2019 |
| Explainable AI for time series classification: a review, taxonomy and research directions A Theissler, F Spinnato, U Schlegel, R Guidotti IEEE Access 10, 100700-100724, 2022 | 67 | 2022 |
| Towards XAI: structuring the processes of explanations M El-Assady, W Jentner, R Kehlbeck, U Schlegel, R Sevastjanova, ... Proceedings of the ACM Workshop on Human-Centered Machine Learning, Glasgow …, 2019 | 37 | 2019 |
| Ts-mule: Local interpretable model-agnostic explanations for time series forecast models U Schlegel, DL Vo, DA Keim, D Seebacher Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 21 | 2021 |
| Time series model attribution visualizations as explanations U Schlegel, DA Keim 2021 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX), 27-31, 2021 | 19 | 2021 |
| Task-based visual interactive modeling: Decision trees and rule-based classifiers D Streeb, Y Metz, U Schlegel, B Schneider, M El-Assady, H Neth, M Chen, ... IEEE Transactions on Visualization and Computer Graphics 28 (9), 3307-3323, 2021 | 18 | 2021 |
| Multiscale snapshots: Visual analysis of temporal summaries in dynamic graphs E Cakmak, U Schlegel, D Jäckle, D Keim, T Schreck IEEE Transactions on Visualization and Computer Graphics 27 (2), 517-527, 2020 | 17 | 2020 |
| An empirical study of explainable AI techniques on deep learning models for time series tasks U Schlegel, D Oelke, DA Keim, M El-Assady arXiv preprint arXiv:2012.04344, 2020 | 16 | 2020 |
| Semantic color mapping: A pipeline for assigning meaningful colors to text M El-Assady, R Kehlbeck, Y Metz, U Schlegel, R Sevastjanova, F Sperrle, ... 2022 IEEE 4th Workshop on Visualization Guidelines in Research, Design, and …, 2022 | 6 | 2022 |
| SpatialRugs: A compact visualization of space and time for analyzing collective movement data JF Buchmüller, U Schlegel, E Cakmak, DA Keim, E Dimara Computers & Graphics 101, 23-34, 2021 | 6 | 2021 |
| SpatialRugs: Enhancing spatial awareness of movement in dense pixel visualizations JF Buchmüller, U Schlegel, E Cakmak, E Dimara, DA Keim arXiv preprint arXiv:2003.12282, 2020 | 6 | 2020 |
| Towards visual debugging for multi-target time series classification U Schlegel, E Cakmak, H Arnout, M El-Assady, D Oelke, DA Keim Proceedings of the 25th International Conference on Intelligent User …, 2020 | 6 | 2020 |
| Modelspex: Model specification using explainable artificial intelligence methods U Schlegel, E Cakmak, DA Keim | 6 | 2020 |
| Human trust modeling for bias mitigation in artificial intelligence F Sperrle, U Schlegel, M El-Assady, DA Keim | 6 | 2019 |
| RescueMark: Visual Analytics of social media data for guiding emergency response in disaster situations: Award for skillful integration of language model A Jeitler, A Türkoglu, D Makarov, T Jockers, J Buchmüller, U Schlegel, ... 2019 IEEE Conference on Visual Analytics Science and Technology (VAST), 120-121, 2019 | 5 | 2019 |
| G-Rap: Interactive text synthesis using recurrent neural network suggestions U Schlegel, E Cakmak, JF Buchmüller, DA Keim | 5 | 2018 |
| A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI U Schlegel, DA Keim World Conference on Explainable Artificial Intelligence, 165-180, 2023 | 4 | 2023 |
| Towards Crime Forecasting Using Deep Learning U Schlegel | 4 | 2018 |
| A comprehensive workflow for effective imitation and reinforcement learning with visual analytics Y Metz, U Schlegel, D Seebacher, M El-Assady, DA Keim | 3 | 2022 |
Daniel KeimProfessor of Computer Science, Data Analysis and Visualization, University of Konstanz在 uni-konstanz.de 的电子邮件经过验证
