4 citations · 13 across the 13 of their papers we have counts for
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Finding the DeepDream for Time Series: Activation Maximization for Univariate Time Series
Udo Schlegel, Daniel A. Keim, Tobias Sutter
Understanding how models process and interpret time series data remains a significant challenge in deep learning to enable applicability in safety-critical areas such as healthcare…
Introducing the Attribution Stability Indicator: a Measure for Time Series XAI Attributions
Udo Schlegel, Daniel A. Keim
Given the increasing amount and general complexity of time series data in domains such as finance, weather forecasting, and healthcare, there is a growing need for state-of-the-art…
RLHF-Blender: A Configurable Interactive Interface for Learning from Diverse Human Feedback
Yannick Metz, David Lindner, Raphaël Baur +2
To use reinforcement learning from human feedback (RLHF) in practical applications, it is crucial to learn reward models from diverse sources of human feedback and to consider huma…
BARReL: Bottleneck Attention for Adversarial Robustness in Vision-Based Reinforcement Learning
Eugene Bykovets, Yannick Metz, Mennatallah El-Assady +2
Robustness to adversarial perturbations has been explored in many areas of computer vision. This robustness is particularly relevant in vision-based reinforcement learning, as the…