6 citations · 33 across the 16 of their papers we have counts for
14 papers
Informed Pre-Training on Prior Knowledge
Laura von Rueden, Sebastian Houben, Kostadin Cvejoski +2
When training data is scarce, the incorporation of additional prior knowledge can assist the learning process. While it is common to initialize neural networks with weights that ha…
Towards Bundle Adjustment for Satellite Imaging via Quantum Machine Learning
Nico Piatkowski, Thore Gerlach, Romain Hugues +3
Given is a set of images, where all images show views of the same area at different points in time and from different viewpoints. The task is the alignment of all images such that…
QUBOs for Sorting Lists and Building Trees
Christian Bauckhage, Thore Gerlach, Nico Piatkowski
We show that the fundamental tasks of sorting lists and building search trees or heaps can be modeled as quadratic unconstrained binary optimization problems (QUBOs). The idea is t…
Street-Map Based Validation of Semantic Segmentation in Autonomous Driving
Laura von Rueden, Tim Wirtz, Fabian Hueger +3
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness, which motivates the thorough validation of learned models. However, current v…
Recurrent Point Review Models
Kostadin Cvejoski, Ramses J. Sanchez, Bogdan Georgiev +2
Deep neural network models represent the state-of-the-art methodologies for natural language processing. Here we build on top of these methodologies to incorporate temporal informa…
Towards Map-Based Validation of Semantic Segmentation Masks
Laura von Rueden, Tim Wirtz, Fabian Hueger +2
Artificial intelligence for autonomous driving must meet strict requirements on safety and robustness. We propose to validate machine learning models for self-driving vehicles not…