Edge Contraction Pooling for Graph Neural Networks F Diehl arXiv preprint arXiv:1905.10990, 2019 | 147 | 2019 |
Graph neural networks for modelling traffic participant interaction F Diehl, T Brunner, M Truong Le, A Knoll 2019 IEEE Intelligent Vehicles Symposium (IV), 695-701, 2019 | 146 | 2019 |
Guessing smart: Biased sampling for efficient black-box adversarial attacks T Brunner, F Diehl, MT Le, A Knoll Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 139 | 2019 |
Uncertainty estimation for deep neural object detectors in safety-critical applications M Truong Le, F Diehl, T Brunner, A Knoll 2018 21st International Conference on Intelligent Transportation Systems …, 2018 | 95 | 2018 |
Deep neural networks for Markovian interactive scene prediction in highway scenarios D Lenz, F Diehl, MT Le, A Knoll 2017 IEEE Intelligent Vehicles Symposium (IV), 685-692, 2017 | 86 | 2017 |
Adversarial vision challenge W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ... The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020 | 64 | 2020 |
Towards Graph Pooling by Edge Contraction F Diehl, T Brunner, M Truong Le, A Knoll ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data, 2019 | 53 | 2019 |
Neural networks for safety-critical applications—Challenges, experiments and perspectives CH Cheng, F Diehl, G Hinz, Y Hamza, G Nührenberg, M Rickert, H Ruess, ... 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2018 | 41 | 2018 |
Warm-Starting AC Optimal Power Flow with Graph Neural Networks F Diehl Climate Change Workshop at the 33rd Conference on Neural Information …, 0 | 27* | |
Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving T Kessler, J Bernhard, M Buechel, K Esterle, P Hart, D Malovetz, MT Le, ... 2019 IEEE Intelligent Vehicles Symposium (IV), 1612-1619, 2019 | 26 | 2019 |
Traceability of deep neural networks V Aravantinos, F Diehl arXiv preprint arXiv:1812.06744, 2018 | 18 | 2018 |
Designing a far-reaching view for highway traffic scenarios with 5G-based intelligent infrastructure G Hinz, M Büchel, F Diehl, M Schellmann, A Knoll 8. Tagung Fahrerassistenz, 2017 | 18 | 2017 |
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks T Brunner, F Diehl, A Knoll arXiv preprint arXiv:1906.06086, 2019 | 9 | 2019 |
Leveraging Semantic Embeddings for Safety-Critical Applications T Brunner, F Diehl, M Truong Le, A Knoll Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 6 | 2019 |
Tree Memory Networks for Sequence Processing F Diehl, A Knoll Artificial Neural Networks and Machine Learning–ICANN 2019: Theoretical …, 2019 | 2 | 2019 |
ML-based tactile sensor calibration: A universal approach M Karl, A Lohrer, D Shah, F Diehl, M Fiedler, S Ognawala, J Bayer, ... arXiv preprint arXiv:1606.06588, 2016 | 2 | 2016 |
apsis-Framework for Automated Optimization of Machine Learning Hyper Parameters F Diehl, A Jauch arXiv preprint arXiv:1503.02946, 2015 | 2 | 2015 |
Applying Graph Neural Networks on Heterogeneous Nodes and Edge Features F Diehl Graph Representation Learning Workshop at 33rd Conference on Neural …, 0 | 1* | |
Relational Representation Learning Beyond Simple Graphs F Gerzer Technische Universität München, 2021 | | 2021 |