| Winning the Lottery Ahead of Time: Efficient Early Network Pruning J Rachwan, D Zügner, B Charpentier, S Geisler, M Ayle, S Günnemann International Conference on Machine Learning, 18293-18309, 2022 | 21 | 2022 |
| BAR-A Reinforcement Learning Agent for Bounding-Box Automated Refinement. M Ayle, J Tekli, J El Zini, B El Asmar, M Awad AAAI, 2561-2568, 2020 | 9 | 2020 |
| On the Robustness and Anomaly Detection of Sparse Neural Networks M Ayle, B Charpentier, J Rachwan, D Zügner, S Geisler, S Günnemann Sparsity in Neural Networks Workshop, 2022 | 6 | 2022 |
| Training Differentially Private Graph Neural Networks with Random Walk Sampling M Ayle, J Schuchardt, L Gosch, D Zügner, S Günnemann Workshop on Trustworthy and Socially Responsible Machine Learning, NeurIPS 2022, 0 | 5* | |
| End-to-End Learning of Probabilistic Hierarchies on Graphs D Zügner, B Charpentier, M Ayle, S Geringer, S Günnemann International Conference on Learning Representations, 2021 | 3 | 2021 |
| Active Scene Understanding for Video Labeling M Ayle, A Döring, A Goncharov, MSS Khan, J Rachwan, MMSK Wong, ... | | 2021 |
John RachwanMaster of Science in Data Engineering and Analytics, Technical University MunichVerified email at tum.de
