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Technische Universität München
Technische Universität München

Foto von Frederik Diehl

Frederik Diehl

Technische Universität München

Informatik 6 - Lehrstuhl für Robotik, Künstliche Intelligenz und Echtzeitsysteme (Prof. Knoll)

Research Interests

My research interest lies in Deep Learning, in particular concentrating on applying them to structured data that's not the ubiquitous image or sequence data. I am therefore concentrating on Graph Neural Networks.

Publications

2020

  • Brendel, Wieland; Rauber, Jonas; Kurakin, Alexey; Papernot, Nicolas; Veliqi, Behar; Mohanty, Sharada P.; Laurent, Florian; Salathé, Marcel; Bethge, Matthias; Yu, Yaodong; Zhang, Hongyang; Xu, Susu; Zhang, Hongbao; Xie, Pengtao; Xing, Eric P.; Brunner, Thomas; Diehl, Frederik; Rony, Jérôme; Hafemann, Luiz Gustavo; Cheng, Shuyu; Dong, Yinpeng; Ning, Xuefei; Li, Wenshuo; Wang, Yu: Adversarial Vision Challenge. In: Escalera, Sergio; Herbrich, Ralf (Hrsg.): The NeurIPS '18 Competition. Springer International Publishing, 2020, 129-153 mehr… BibTeX Volltext ( DOI )

2019

  • Brunner, Thomas; Diehl, Frederik; Knoll, Alois: Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , 2019Long Beach, CA, USA mehr… BibTeX Volltext (mediaTUM)
  • Brunner, Thomas; Diehl, Frederik; Truong Le, Michael; Knoll, Alois: Leveraging Semantic Embeddings for Safety-Critical Applications. 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, 2019Long Beach, CA, USA, 1389-1394 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Brunner, Thomas; Diehl, Frederik; Truong Le, Michael; Knoll, Alois: Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. 2019 IEEE/CVF International Conference on Computer Vision (ICCV), IEEE, 2019Seoul, South Korea, 4957-4965 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Diehl, Frederik: Edge Contraction Pooling for Graph Neural Networks. CoRR abs/1905.10990, 2019 mehr… BibTeX
  • Frederik Diehl, Thomas Brunner, Michael Truong Le and Alois Knoll: Towards Graph Pooling by Edge Contraction. ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data, 2019 mehr… BibTeX Volltext (mediaTUM)
  • Frederik Diehl, Thomas Brunner, Michael Truong Le, Alois Knoll: Graph Neural Networks for Modelling Traffic Participant Interaction. IEEE Intelligent Vehicles Symposium 2019, 2019 mehr… BibTeX Volltext (mediaTUM)
  • Kessler, Tobias; Bernhard, Julian; Buechel, Martin; Esterle, Klemens; Hart, Patrick; Malovetz, Daniel; Truong Le, Michael; Diehl, Frederik; Brunner, Thomas; Knoll, Alois: Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving. 2019 IEEE Intelligent Vehicles Symposium (IV), IEEE, 2019 mehr… BibTeX Volltext ( DOI )

2018

  • Cheng, Chih-Hong; Diehl, Frederik; Hinz, Gereon; Hamza, Yassine; Nührenberg, Georg; Rickert, Markus; Rueß, Harald; Truong-Le, Michael: Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives. Proceedings of the Design, Automation & Test in Europe Conference & Exhibition (DATE), 2018 mehr… BibTeX Volltext ( DOI ) Volltext (mediaTUM)
  • Michael Truong Le, Frederik Diehl, Thomas Brunner, Alois Knoll: Uncertainty Estimation for Deep Neural Object Detectors in Safety-Critical Applications. International Conference on Intelligent Transportation Systems 2018, 2018 mehr… BibTeX Volltext (mediaTUM)
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