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ORCIDFrederik Diehl
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2010 – 2019
- 2019
[c8]Thomas Brunner
, Frederik Diehl, Michael Truong-Le, Alois C. Knoll:
Leveraging Semantic Embeddings for Safety-Critical Applications. CVPR Workshops 2019: 1389-1394- [c7]Frederik Diehl, Alois C. Knoll:
Tree Memory Networks for Sequence Processing. ICANN (1) 2019: 431-443 - [c6]Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll:
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. ICCV 2019: 4957-4965 - [c5]Frederik Diehl, Thomas Brunner, Michael Truong-Le, Alois C. Knoll:
Graph Neural Networks for Modelling Traffic Participant Interaction. IV 2019: 695-701 - [c4]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: 1612-1619 - [i9]Frederik Diehl, Thomas Brunner, Michael Truong-Le, Alois C. Knoll:
Graph Neural Networks for Modelling Traffic Participant Interaction. CoRR abs/1903.01254 (2019) - [i8]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 abs/1905.02980 (2019) - [i7]Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll:
Leveraging Semantic Embeddings for Safety-Critical Applications. CoRR abs/1905.07733 (2019) - [i6]Frederik Diehl:
Edge Contraction Pooling for Graph Neural Networks. CoRR abs/1905.10990 (2019) - [i5]Thomas Brunner, Frederik Diehl, Alois C. Knoll:
Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks. CoRR abs/1906.06086 (2019) - 2018
- [c3]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: 1005-1006 - [c2]Michael Truong-Le, Frederik Diehl, Thomas Brunner, Alois C. Knoll:
Uncertainty Estimation for Deep Neural Object Detectors in Safety-Critical Applications. ITSC 2018: 3873-3878 - [i4]Thomas Brunner, Frederik Diehl, Michael Truong-Le, Alois C. Knoll:
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. CoRR abs/1812.09803 (2018) - 2017
- [c1]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: 685-692 - [i3]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 abs/1709.00911 (2017) - 2016
- [i2]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 abs/1606.06588 (2016) - 2015
- [i1]Frederik Diehl, Andreas Jauch:
apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters. CoRR abs/1503.02946 (2015)
Coauthor Index
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