| Higher-order explanations of graph neural networks via relevant walks T Schnake, O Eberle, J Lederer, S Nakajima, KT Schütt, KR Müller, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 227* | 2021 |
| Self-attentive, multi-context one-class classification for unsupervised anomaly detection on text L Ruff, Y Zemlyanskiy, R Vandermeulen, T Schnake, M Kloft Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 68 | 2019 |
| XAI for transformers: Better explanations through conservative propagation A Ali, T Schnake, O Eberle, G Montavon, KR Müller, L Wolf International Conference on Machine Learning, 435-451, 2022 | 60 | 2022 |
| Efficient computation of higher-order subgraph attribution via message passing P Xiong, T Schnake, G Montavon, KR Müller, S Nakajima International Conference on Machine Learning, 24478-24495, 2022 | 3 | 2022 |
| Relevant walk search for explaining graph neural networks P Xiong, T Schnake, M Gastegger, G Montavon, KR Muller, S Nakajima International Conference on Machine Learning, 38301-38324, 2023 | 1 | 2023 |
| Efficient Higher-Order Subgraph Attribution via Message Passing P Xiong, T Schnake, G Montavon, KR Müller, S Nakajima MA thesis. Technische Universität Berlin, 2022 | 1 | 2022 |
| Synthesis of High-Resolution Load Profiles with Minimal Data T Schnake, D Bauer arXiv preprint arXiv:1903.06625, 2019 | | 2019 |
