| Explainability and Adversarial Robustness for RNNs A Hartl, M Bachl, J Fabini, T Zseby BigDataService 2020, 2019 | 47 | 2019 |
| A flow-based IDS using Machine Learning in eBPF M Bachl, J Fabini, T Zseby arXiv preprint arXiv:2102.09980, 2021 | 35 | 2021 |
| A meta-analysis approach for feature selection in network traffic research DC Ferreira, FI Vázquez, G Vormayr, M Bachl, T Zseby Proceedings of the Reproducibility Workshop, 17-20, 2017 | 26 | 2017 |
| Walling up Backdoors in Intrusion Detection Systems M Bachl, A Hartl, J Fabini, T Zseby Big-DAMA '19, 8-13, 2019 | 23 | 2019 |
| Rax: Deep reinforcement learning for congestion control M Bachl, T Zseby, J Fabini ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 21 | 2019 |
| City-GAN: Learning architectural styles using a custom Conditional GAN architecture M Bachl, DC Ferreira arXiv preprint arXiv:1907.05280, 2019 | 17 | 2019 |
| NTARC: a data model for the systematic review of network traffic analysis research F Iglesias, DC Ferreira, G Vormayr, M Bachl, T Zseby Applied Sciences 10 (12), 4307, 2020 | 12 | 2020 |
| SparseIDS: Learning Packet Sampling with Reinforcement Learning M Bachl, F Meghdouri, J Fabini, T Zseby SPC 2020, 2020 | 11 | 2020 |
| LFQ: Online Learning of Per-flow Queuing Policies using Deep Reinforcement Learning M Bachl, J Fabini, T Zseby LCN 2020, 2020 | 9 | 2020 |
| Cocoa: Congestion Control Aware Queuing M Bachl, J Fabini, T Zseby Workshop on Buffer Sizing, 2019, 2019 | 8 | 2019 |
| EagerNet: Early Predictions of Neural Networks for Computationally Efficient Intrusion Detection F Meghdouri, M Bachl, T Zseby CSNet 2020, 2020 | 5 | 2020 |
| Fair Queuing Aware Congestion Control M Bachl arXiv preprint arXiv:2206.10561, 2022 | 2 | 2022 |
| Detecting Fair Queuing for Better Congestion Control M Bachl, J Fabini, T Zseby arXiv preprint arXiv:2010.08362, 2020 | 2* | 2020 |
| Curated Research on Network Traffic Analysis DC Ferreira, M Bachl, G Vormayr, FI Vázquez, T Zseby Data set]. Zenodo., Nov, 2018 | 2 | 2018 |
| Impact of packet loss on localization and subjective quality in 3D-telephone calls M Bachl Bachelor Thesis. Quality and Usability Lab, Technische Universität Berlin …, 2014 | 2 | 2014 |
| Machine Learning Methods for Communication Networks: Characterization of Requirements and Analysis of Selected Use Cases M Bachl TU Wien, 2021 | 1* | 2021 |
| Collaborative Home Network Troubleshooting M Bachl Université Pierre & Marie Curie-Paris 6; INRIA, 2016 | 1 | 2016 |
| (007) COMPREHENSIVE SEXUALITY EDUCATION POSITIVE IMPACT ON HIV PREVALENCE AND HIV PREVENTIVE MEASURES KNOWLEDGE AMONGST YOUNG PEOPLE AGED 15-24 YEARS OLD-A GLOBAL STUDY OF 181 … G Sansoni, M Bachl, N Pitla, F Chiara The Journal of Sexual Medicine 21 (Supplement_6), qdae161. 007, 2024 | | 2024 |
| Robo99: Readability-optimized Comic Sans alternative using Machine Learning M Bachl https://muxamilian.github.io/Robo99/, 2023 | | 2023 |
| What you see is what you hear M Bachl https://github.com/muxamilian/wysiwyh, 2022 | | 2022 |
Tanja ZsebyTU WienE-mail confirmado em tuwien.ac.at
