1 code implementation • 14 Jun 2019 • Thomas Brunner, Frederik Diehl, Alois Knoll
Many optimization methods for generating black-box adversarial examples have been proposed, but the aspect of initializing said optimizers has not been considered in much detail.
no code implementations • 27 May 2019 • Frederik Diehl
Graph Neural Network (GNN) research has concentrated on improving convolutional layers, with little attention paid to developing graph pooling layers.
Ranked #74 on Graph Classification on PROTEINS
no code implementations • 19 May 2019 • Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll
Semantic Embeddings are a popular way to represent knowledge in the field of zero-shot learning.
no code implementations • 4 Mar 2019 • Frederik Diehl, Thomas Brunner, Michael Truong Le, Alois Knoll
We show that prediction error in scenarios with much interaction decreases by 30% compared to a model that does not take interactions into account.
3 code implementations • ICCV 2019 • Thomas Brunner, Frederik Diehl, Michael Truong Le, Alois Knoll
We consider adversarial examples for image classification in the black-box decision-based setting.
no code implementations • 17 Dec 2018 • Vincent Aravantinos, Frederik Diehl
We investigate which artifacts could play a similar role to code or low-level requirements in neural network development and propose various traces which one could possibly consider as a replacement for classical notions.
no code implementations • 4 Sep 2017 • Chih-Hong Cheng, Frederik Diehl, Yassine Hamza, Gereon Hinz, Georg Nührenberg, Markus Rickert, Harald Ruess, Michael Troung-Le
We propose a methodology for designing dependable Artificial Neural Networks (ANN) by extending the concepts of understandability, correctness, and validity that are crucial ingredients in existing certification standards.
no code implementations • 21 Jun 2016 • Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt
We study the responses of two tactile sensors, the fingertip sensor from the iCub and the BioTac under different external stimuli.
1 code implementation • 10 Mar 2015 • Frederik Diehl, Andreas Jauch
The apsis toolkit presented in this paper provides a flexible framework for hyperparameter optimization and includes both random search and a bayesian optimizer.