| NF-GNN: network flow graph neural networks for malware detection and classification J Busch, A Kocheturov, V Tresp, T Seidl Proceedings of the 33rd International Conference on Scientific and …, 2021 | 34 | 2021 |
| PushNet: Efficient and Adaptive Neural Message Passing J Busch, J Pi, T Seidl 24th European Conference on Artificial Intelligence (ECAI 2020), 1039-1046, 2020 | 14* | 2020 |
| Structural graph representations based on multiscale local network topologies F Borutta, J Busch, E Faerman, A Klink, M Schubert IEEE/WIC/ACM International Conference on Web Intelligence, 91-98, 2019 | 6 | 2019 |
| Semi-supervised learning on graphs based on local label distributions E Faerman, F Borutta, J Busch, M Schubert 14th International Workshop on Mining and Learning with Graphs (MLG'18), 2018 | 6 | 2018 |
| Learning self-expression metrics for scalable and inductive subspace clustering J Busch, E Faerman, M Schubert, T Seidl NeurIPS 2020 Workshop: Self-Supervised Learning - Theory and Practice, 2020 | 5 | 2020 |
| DiffusAL: Coupling Active Learning with Graph Diffusion for Label-Efficient Node Classification S Gilhuber, J Busch, D Rotthues, CMM Frey, T Seidl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 2 | 2023 |
| Implicit Hough Transform Neural Networks for Subspace Clustering J Busch, M Hünemörder, J Held, P Kröger, T Seidl 2021 International Conference on Data Mining Workshops (ICDMW), 441-448, 2021 | 2 | 2021 |
| Ada-lld: adaptive node similarity using multi-scale local label distributions E Faerman, F Borutta, J Busch, M Schubert 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and …, 2020 | 2 | 2020 |
| Grace-Limiting the Number of Grid Cells for Clustering High-Dimensional Data. A Beer, D Kazempour, J Busch, A Tekles, T Seidl LWDA, 11-22, 2020 | 2 | 2020 |
| Continuous Simulation with Ordinary Differential Equations J Busch University of Hamburg: Hamburg, Germany, 2013 | 2 | 2013 |
| Representation learning on complex data J Busch lmu, 2021 | | 2021 |
