Leonid Schwenke
Orcid: 0000-0002-2337-3905
According to our database1,
Leonid Schwenke authored at least 14 papers
between 2016 and 2025.
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Bibliography
2025
Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions.
CoRR, January, 2025
Evaluating Higher-Level and Symbolic Features in Deep Learning on Time Series: Towards Simpler Explainability.
Proceedings of the Advances in Computational Intelligence, 2025
A Global Dataset-Specific Any-Order Minimal Expectation Baseline for Saliency Scores.
Proceedings of the 12th IEEE International Conference on Data Science and Advanced Analytics, 2025
Evaluating Interpretability Using Logical Relations: Do Saliency Maps Encode Relevant Information?
Proceedings of the 12th IEEE International Conference on Data Science and Advanced Analytics, 2025
2024
CoRR, 2024
2023
Extracting Interpretable Local and Global Representations from Attention on Time Series.
CoRR, 2023
Identifying Informative Nodes in Attributed Spatial Sensor Networks Using Attention for Symbolic Abstraction in a GNN-based Modeling Approach.
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023
Making Time Series Embeddings More Interpretable in Deep Learning - Extracting Higher-Level Features via Symbolic Approximation Representations.
Proceedings of the Thirty-Sixth International Florida Artificial Intelligence Research Society Conference, 2023
2021
Using Brain Activity Patterns to Differentiate Real and Virtual Attended Targets during Augmented Reality Scenarios.
Inf., 2021
Real or Virtual? Using Brain Activity Patterns to differentiate Attended Targets during Augmented Reality Scenarios.
CoRR, 2021
Abstracting Local Transformer Attention for Enhancing Interpretability on Time Series Data.
Proceedings of the LWDA 2021 Workshops: FGWM, 2021
Show Me What You're Looking For Visualizing Abstracted Transformer Attention for Enhancing Their Local Interpretability on Time Series Data.
Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021
Constructing Global Coherence Representations: Identifying Interpretability and Coherences of Transformer Attention in Time Series Data.
Proceedings of the 8th IEEE International Conference on Data Science and Advanced Analytics, 2021
2016