| A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts G Schwalbe, B Finzel Data Mining and Knowledge Discovery, 1-59, 2023 | 120* | 2023 |
| A survey on methods for the safety assurance of machine learning based systems G Schwalbe, M Schels 10th European Congress on Embedded Real Time Software and Systems (ERTS 2020), 2020 | 55 | 2020 |
| Inspect, understand, overcome: A survey of practical methods for ai safety S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ... Deep Neural Networks and Data for Automated Driving: Robustness, Uncertainty …, 2022 | 54 | 2022 |
| Structuring the safety argumentation for deep neural network based perception in automotive applications G Schwalbe, B Knie, T Sämann, T Dobberphul, L Gauerhof, S Raafatnia, ... Computer Safety, Reliability, and Security. SAFECOMP 2020 Workshops: DECSoS …, 2020 | 27 | 2020 |
| Expressive explanations of DNNs by combining concept analysis with ILP J Rabold, G Schwalbe, U Schmid KI 2020: Advances in Artificial Intelligence: 43rd German Conference on AI …, 2020 | 21 | 2020 |
| Concept embedding analysis: A review G Schwalbe arXiv preprint arXiv:2203.13909, 2022 | 20 | 2022 |
| Concept enforcement and modularization as methods for the ISO 26262 safety argumentation of neural networks G Schwalbe, M Schels Otto-Friedrich-Universität, 2020 | 16 | 2020 |
| Evaluating the stability of semantic concept representations in CNNs for robust explainability G Mikriukov, G Schwalbe, C Hellert, K Bade World Conference on Explainable Artificial Intelligence, 499-524, 2023 | 4 | 2023 |
| Interpretable model-agnostic plausibility verification for 2d object detectors using domain-invariant concept bottleneck models M Keser, G Schwalbe, A Nowzad, A Knoll Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
| Verification of size invariance in DNN activations using concept embeddings G Schwalbe IFIP International Conference on Artificial Intelligence Applications and …, 2021 | 4 | 2021 |
| Strategies for safety goal decomposition for neural networks G Schwalbe, M Schels Abstracts 3rd ACM Computer Science in Cars Symposium, 2019 | 3 | 2019 |
| Enabling Verification of Deep Neural Networks in Perception Tasks Using Fuzzy Logic and Concept Embeddings G Schwalbe, C Wirth, U Schmid arXiv preprint arXiv:2201.00572, 2022 | 2* | 2022 |
| GCPV: Guided Concept Projection Vectors for the Explainable Inspection of CNN Feature Spaces G Mikriukov, G Schwalbe, C Hellert, K Bade arXiv preprint arXiv:2311.14435, 2023 | 1 | 2023 |
| Quantified Semantic Comparison of Convolutional Neural Networks G Mikriukov, G Schwalbe, C Hellert, K Bade arXiv preprint arXiv:2305.07663, 2023 | 1 | 2023 |
| The Anatomy of Adversarial Attacks: Concept-based XAI Dissection G Mikriukov, G Schwalbe, F Motzkus, K Bade arXiv preprint arXiv:2403.16782, 2024 | | 2024 |
| Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes Y Shoeb, R Chan, G Schwalbe, A Nowzad, F Güney, H Gottschalk Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | | 2024 |
| Method for monitoring logical consistency in a machine learning model and associated monitoring device G Schwalbe, C Wirth US Patent App. 18/046,087, 2023 | | 2023 |
| Concept Embedding Analysis Based Methods for the Safety Assurance of Deep Neural Networks: towards safe automotive computer vision applications G Schwalbe Otto-Friedrich-Universität Bamberg, Fakultät Wirtschaftsinformatik und …, 2022 | | 2022 |
| Concept Enforcement and Modularization for the ISO 26262 Safety Case of Neural Networks G Schwalbe, U Schmid Otto-Friedrich-Universität, 2019 | | 2019 |
| 1.13 Object Detection Plausibility with Concept-Bottleneck Models M Keser, G Schwalbe, A Nowzad, C AG | | |
Bettina FinzelCognitive Systems' Doctoral Candidate and BaCAI member, University of BambergVerified email at uni-bamberg.de
