5 citations · 10 across the 7 of their papers we have counts for
7 papers
Simulating Human Gaze with Neural Visual Attention
Leo Schwinn, Doina Precup, Bjoern Eskofier +1
Existing models of human visual attention are generally unable to incorporate direct task guidance and therefore cannot model an intent or goal when exploring a scene. To integrate…
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-in…
Active Learning of Ordinal Embeddings: A User Study on Football Data
Christoffer Loeffler, Kion Fallah, Stefano Fenu +4
Humans innately measure distance between instances in an unlabeled dataset using an unknown similarity function. Distance metrics can only serve as proxy for similarity in informat…
Behind the Machine's Gaze: Neural Networks with Biologically-inspired Constraints Exhibit Human-like Visual Attention
Leo Schwinn, Doina Precup, Björn Eskofier +1
By and large, existing computational models of visual attention tacitly assume perfect vision and full access to the stimulus and thereby deviate from foveated biological vision. M…
How to Learn from Risk: Explicit Risk-Utility Reinforcement Learning for Efficient and Safe Driving Strategies
Lukas M. Schmidt, Sebastian Rietsch, Axel Plinge +2
Autonomous driving has the potential to revolutionize mobility and is hence an active area of research. In practice, the behavior of autonomous vehicles must be acceptable, i.e., e…
Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series
Christoffer Loeffler, Wei-Cheng Lai, Bjoern Eskofier +3
The correct interpretation of convolutional models is a hard problem for time series data. While saliency methods promise visual validation of predictions for image and language pr…
An Introduction to Multi-Agent Reinforcement Learning and Review of its Application to Autonomous Mobility
Lukas M. Schmidt, Johanna Brosig, Axel Plinge +2
Many scenarios in mobility and traffic involve multiple different agents that need to cooperate to find a joint solution. Recent advances in behavioral planning use Reinforcement L…