| DropGNN: Random dropouts increase the expressiveness of graph neural networks PA Papp, K Martinkus, L Faber, R Wattenhofer Advances in Neural Information Processing Systems 34, 21997-22009, 2021 | 168 | 2021 |
| When Comparing to Ground Truth is Wrong: On Evaluating GNN Explanation Methods L Faber, A K. Moghaddam, R Wattenhofer Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 69 | 2021 |
| Personalized Knowledge Graph Summarization: From the Cloud to Your Pocket T Safavi, C Belth, L Faber, D Mottin, E Müller, D Koutra Ieee International Conference on Data Mining, 2019 | 57 | 2019 |
| Towards Robust Graph Contrastive Learning N Jovanović, Z Meng, L Faber, R Wattenhofer arXiv preprint arXiv:2102.13085, 2021 | 45 | 2021 |
| Contrastive graph neural network explanation L Faber, AK Moghaddam, R Wattenhofer arXiv preprint arXiv:2010.13663, 2020 | 39 | 2020 |
| GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks P Müller, L Faber, K Martinkus, R Wattenhofer The Twelfth International Conference on Learning Representations, 2023 | 14* | 2023 |
| Should Graph Neural Networks Use Features, Edges, Or Both? L Faber, Y Lu, R Wattenhofer arXiv preprint arXiv:2103.06857, 2021 | 10 | 2021 |
| Neural status registers L Faber, R Wattenhofer International Conference on Machine Learning, 9508-9522, 2023 | 8 | 2023 |
| Adaptive Personalized Knowledge Graph Summarization L Faber, T Safavi, D Mottin, E Müller, D Koutra Proceedings of the 14th International KDD Workshop on Mining and Learning …, 2018 | 7 | 2018 |
| GwAC: GNNs with Asynchronous Communication L Faber, R Wattenhofer The Second Learning on Graphs Conference, 2023 | 3 | 2023 |
| Asynchronous Neural Networks for Learning in Graphs L Faber, R Wattenhofer arXiv preprint arXiv:2205.12245, 2022 | 3 | 2022 |
| Low redundancy estimation of correlation matrices for time series using triangular bounds E Scharwächter, F Geier, L Faber, E Müller Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia …, 2018 | 2 | 2018 |
| Learning Lower Bounds for Graph Exploration With Reinforcement Learning J Elmiger, L Faber, P Khanchandani, O Richter, R Wattenhofer | 1 | 2020 |
| A Tissue-aware Gene Selection Approach for Analyzing Multi-tissue Gene Expression Data C Perscheid, L Faber, M Kraus, P Arndt, M Janke, S Rehfeldt, A Schubotz, ... 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 1 | 2018 |
| Medley2K: A Dataset of Medley Transitions L Faber, S Luck, D Pascual, A Roth, G Brunner, R Wattenhofer arXiv preprint arXiv:2008.11159, 2020 | | 2020 |
| Serving Live Multimedia for the Linked Open Data Cloud S Serth, S Haarmann, L Faber Gesellschaft für Informatik, Bonn, 2017 | | 2017 |
