9 citations · 19 across the 6 of their papers we have counts for
8 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…
Just a Matter of Scale? Reevaluating Scale Equivariance in Convolutional Neural Networks
Thomas Altstidl, An Nguyen, Leo Schwinn +4
The widespread success of convolutional neural networks may largely be attributed to their intrinsic property of translation equivariance. However, convolutions are not equivariant…
Improving Robustness against Real-World and Worst-Case Distribution Shifts through Decision Region Quantification
Leo Schwinn, Leon Bungert, An Nguyen +5
The reliability of neural networks is essential for their use in safety-critical applications. Existing approaches generally aim at improving the robustness of neural networks to e…
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks
Leo Schwinn, René Raab, An Nguyen +2
Progress in making neural networks more robust against adversarial attacks is mostly marginal, despite the great efforts of the research community. Moreover, the robustness evaluat…
Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis
Leo Schwinn, An Nguyen, René Raab +5
The susceptibility of deep neural networks to untrustworthy predictions, including out-of-distribution (OOD) data and adversarial examples, still prevent their widespread use in sa…
Time Matters: Time-Aware LSTMs for Predictive Business Process Monitoring
An Nguyen, Srijeet Chatterjee, Sven Weinzierl +3
Predictive business process monitoring (PBPM) aims to predict future process behavior during ongoing process executions based on event log data. Especially, techniques for the next…