Monitoring Android Devices by using Events and Metadata. - Markus Schölzel; Evren Eren; Kai-Oliver Detken; Leonid Schwenke (Int. J. Comput., 2016)

Constructing Global Coherence Representations: Identifying Interpretability and Coherences of Transformer Attention in Time Series Data. - Leonid Schwenke; Martin Atzmueller (DSAA, 2021)

Show Me What You're Looking For Visualizing Abstracted Transformer Attention for Enhancing Their Local Interpretability on Time Series Data. - Leonid Schwenke; Martin Atzmueller (FLAIRS, 2021)

Abstracting Local Transformer Attention for Enhancing Interpretability on Time Series Data. - Leonid Schwenke; Martin Atzmueller (LWDA, 2021)

Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios. - Lisa-Marie Vortmann; Leonid Schwenke; Felix Putze (CoRR, 2021)

Using Brain Activity Patterns to Differentiate Real and Virtual Attended Targets during Augmented Reality Scenarios. - Lisa-Marie Vortmann; Leonid Schwenke; Felix Putze (Inf., 2021)

Making Time Series Embeddings More Interpretable in Deep Learning - Extracting Higher-Level Features via Symbolic Approximation Representations. - Leonid Schwenke; Martin Atzmueller (FLAIRS, 2023)

Identifying Informative Nodes in Attributed Spatial Sensor Networks Using Attention for Symbolic Abstraction in a GNN-based Modeling Approach. - Leonid Schwenke; Stefan Bloemheuvel; Martin Atzmueller (FLAIRS, 2023)

Extracting Interpretable Local and Global Representations from Attention on Time Series. - Leonid Schwenke; Martin Atzmueller (CoRR, 2023)

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation. - Leonid Schwenke; Martin Atzmueller (CoRR, 2024)

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions. - Leonid Schwenke; Martin Atzmueller (CoRR, 2025)