Frederik Diehl

Publication Activity (10 Years)

Years Active: 2015-2019
Publications (10 Years): 17

Top Topics

Safety Analysis

Autonomous Driving

Radially Symmetric

Top Venues

Publications

Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll
Leveraging Semantic Embeddings for Safety-Critical Applications. CoRR (2019)
Frederik Diehl
Edge Contraction Pooling for Graph Neural Networks. CoRR (2019)
Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll
Leveraging Semantic Embeddings for Safety-Critical Applications. CVPR Workshops (2019)
Frederik Diehl, Alois C. Knoll
Tree Memory Networks for Sequence Processing. ICANN (1) (2019)
Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. ICCV (2019)
Frederik Diehl, Thomas Brunner, Michael Truong-Le, Alois C. Knoll
Graph Neural Networks for Modelling Traffic Participant Interaction. IV (2019)
Tobias Kessler, Julian Bernhard, Martin Buechel, Klemens Esterle, Patrick Hart, Daniel Malovetz, Michael Truong-Le, Frederik Diehl, Thomas Brunner, Alois C. Knoll
Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving. CoRR (2019)
Frederik Diehl, Thomas Brunner, Michael Truong-Le, Alois C. Knoll
Graph Neural Networks for Modelling Traffic Participant Interaction. CoRR (2019)
Thomas Brunner, Frederik Diehl, Alois C. Knoll
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks. CoRR (2019)
Tobias Kessler, Julian Bernhard, Martin Buechel, Klemens Esterle, Patrick Hart, Daniel Malovetz, Michael Truong-Le, Frederik Diehl, Thomas Brunner, Alois C. Knoll
Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving. IV (2019)
Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. CoRR (2018)
Chih-Hong Cheng, Frederik Diehl, Gereon Hinz, Yassine Hamza, Georg Nührenberg, Markus Rickert, Harald Ruess, Michael Truong-Le
Neural networks for safety-critical applications - Challenges, experiments and perspectives. DATE (2018)
Michael Truong-Le, Frederik Diehl, Thomas Brunner, Alois C. Knoll
Uncertainty Estimation for Deep Neural Object Detectors in Safety-Critical Applications. ITSC (2018)
Chih-Hong Cheng, Frederik Diehl, Yassine Hamza, Gereon Hinz, Georg Nührenberg, Markus Rickert, Harald Ruess, Michael Truong-Le
Neural Networks for Safety-Critical Applications - Challenges, Experiments and Perspectives. CoRR (2017)
David Lenz, Frederik Diehl, Michael Truong-Le, Alois C. Knoll
Deep neural networks for Markovian interactive scene prediction in highway scenarios. Intelligent Vehicles Symposium (2017)
Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt
ML-based tactile sensor calibration: A universal approach. CoRR (2016)
Frederik Diehl, Andreas Jauch
apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters. CoRR (2015)