33 citations · 200 across the 34 of their papers we have counts for
41 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.…
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…
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI
Udo Schlegel, Daniel A. Keim
Explainable Artificial Intelligence (XAI) has gained significant attention recently as the demand for transparency and interpretability of machine learning models has increased. In…
SkiVis: Visual Exploration and Route Planning in Ski Resorts
Julius Rauscher, Raphael Buchmüller, Daniel A. Keim +1
Optimal ski route selection is a challenge based on a multitude of factors, such as the steepness, compass direction, or crowdedness. The personal preferences of every skier toward…
The Role of Interactive Visualization in Explaining (Large) NLP Models: from Data to Inference
Richard Brath, Daniel Keim, Johannes Knittel +3
With a constant increase of learned parameters, modern neural language models become increasingly more powerful. Yet, explaining these complex model's behavior remains a widely uns…
How to Enable Uncertainty Estimation in Proximal Policy Optimization
Eugene Bykovets, Yannick Metz, Mennatallah El-Assady +2
While deep reinforcement learning (RL) agents have showcased strong results across many domains, a major concern is their inherent opaqueness and the safety of such systems in real…