1 citations · 2 across the 4 of their papers we have counts for
4 papers
Interactive dense pixel visualizations for time series and model attribution explanations
Udo Schlegel, Daniel A. Keim
The field of Explainable Artificial Intelligence (XAI) for Deep Neural Network models has developed significantly, offering numerous techniques to extract explanations from models.…
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…
Visual Explanations with Attributions and Counterfactuals on Time Series Classification
Udo Schlegel, Daniela Oelke, Daniel A. Keim +1
With the rising necessity of explainable artificial intelligence (XAI), we see an increase in task-dependent XAI methods on varying abstraction levels. XAI techniques on a global l…