apsis - Framework for Automated Optimization of Machine Learning Hyper Parameters. - Frederik Diehl; Andreas Jauch (CoRR, 2015)

ML-based tactile sensor calibration: A universal approach. - Maximilian Karl; Artur Lohrer; Dhananjay Shah; Frederik Diehl; Max Fiedler; Saahil Ognawala; Justin Bayer; Patrick van der Smagt (CoRR, 2016)

Deep neural networks for Markovian interactive scene prediction in highway scenarios. - David Lenz 001; Frederik Diehl; Michael Truong-Le; Alois C. Knoll (Intelligent Vehicles Symposium, 2017)

Neural networks for safety-critical applications - Challenges, experiments and perspectives. - Chih-Hong Cheng; Frederik Diehl; Gereon Hinz; Yassine Hamza; Georg Nührenberg; Markus Rickert 001; Harald Ruess; Michael Truong-Le (DATE, 2018)

Uncertainty Estimation for Deep Neural Object Detectors in Safety-Critical Applications. - Michael Truong-Le; Frederik Diehl; Thomas Brunner; Alois C. Knoll (ITSC, 2018)

Leveraging Semantic Embeddings for Safety-Critical Applications. - Thomas Brunner; Frederik Diehl; Michael Truong-Le; Alois C. Knoll (CVPR Workshops, 2019)

Tree Memory Networks for Sequence Processing. - Frederik Diehl; Alois C. Knoll (ICANN (1), 2019)

Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks. - Thomas Brunner; Frederik Diehl; Michael Truong-Le; Alois C. Knoll (ICCV, 2019)

Graph Neural Networks for Modelling Traffic Participant Interaction. - Frederik Diehl; Thomas Brunner; Michael Truong-Le; Alois C. Knoll (IV, 2019)

Bridging the Gap between Open Source Software and Vehicle Hardware for Autonomous Driving. - Tobias Kessler; Julian Bernhard; Martin Buechel; Klemens Esterle; Patrick Hart; Daniel Malovetz; Michael Truong-Le; Frederik Diehl; Thomas Brunner; Alois C. Knoll (IV, 2019)

Edge Contraction Pooling for Graph Neural Networks. - Frederik Diehl (CoRR, 2019)

Copy and Paste: A Simple But Effective Initialization Method for Black-Box Adversarial Attacks. - Thomas Brunner; Frederik Diehl; Alois C. Knoll (CoRR, 2019)