Search Results for author:
Found 3 papers, 1 papers with code
What the Constant Velocity Model Can Teach Us About Pedestrian Motion Prediction
Our work shows how neural networks for pedestrian motion prediction can be thoroughly evaluated and our results indicate which research directions for neural motion prediction are promising in future.
Traceability of Deep Neural Networks
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.
Decidability and Undecidability Results for Propositional Schemata
The satisfiability problem is shown to be undecidable for this new logic, but we introduce a very general class of schemata, called bound-linear, for which this problem becomes decidable.
