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2012.04344
Cited By
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks
8 December 2020
U. Schlegel
Daniela Oelke
Daniel A. Keim
Mennatallah El-Assady
AI4TS
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Papers citing
"An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks"
7 / 7 papers shown
Towards Explainable Deep Clustering for Time Series Data
Udo Schlegel
Gabriel Marques Tavares
Thomas Seidl
AI4TS
OOD
329
1
0
28 Jul 2025
Introducing the Attribution Stability Indicator: a Measure for Time Series XAI Attributions
U. Schlegel
Daniel A. Keim
AI4TS
426
4
0
06 Oct 2023
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI
U. Schlegel
Daniel A. Keim
AAML
AI4TS
368
16
0
11 Jul 2023
Prototypes as Explanation for Time Series Anomaly Detection
Bin Li
Carsten Jentsch
Emmanuel Müller
AI4TS
212
5
0
04 Jul 2023
Towards Explainable Artificial Intelligence in Banking and Financial Services
Ambreen Hanif
146
14
0
14 Dec 2021
Time Series Model Attribution Visualizations as Explanations
U. Schlegel
Daniel A. Keim
TDI
BDL
FAtt
AI4TS
XAI
235
19
0
27 Sep 2021
TS-MULE: Local Interpretable Model-Agnostic Explanations for Time Series Forecast Models
U. Schlegel
D. Lam
Daniel A. Keim
Daniel Seebacher
FAtt
AI4TS
313
44
0
17 Sep 2021
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