Evaluating Simplification Algorithms for Interpretability of Time Series Classification
Fuente:
arXiv
Saved in:
| Main Authors: | Håvardstun, Brigt, Marti-Perez, Felix, Ferri, Cèsar, Telle, Jan Arne |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
On a Combinatorial Problem Arising in Machine Teaching
by: Håvardstun, Brigt, et al.
Published: (2024)
by: Håvardstun, Brigt, et al.
Published: (2024)
Teaching and Learning under Deductive Errors
by: Telle, Jan Arne, et al.
Published: (2026)
by: Telle, Jan Arne, et al.
Published: (2026)
When Redundancy Matters: Machine Teaching of Representations
by: Ferri, Cèsar, et al.
Published: (2024)
by: Ferri, Cèsar, et al.
Published: (2024)
Relative Drawing Identification Complexity is Invariant to Modality in Vision-Language Models
by: Freitas, Diogo, et al.
Published: (2025)
by: Freitas, Diogo, et al.
Published: (2025)
CRITS: Convolutional Rectifier for Interpretable Time Series Classification
by: Kuratomi, Alejandro, et al.
Published: (2025)
by: Kuratomi, Alejandro, et al.
Published: (2025)
Mechanistic Interpretability for Transformer-based Time Series Classification
by: Kalnāre, Matīss, et al.
Published: (2025)
by: Kalnāre, Matīss, et al.
Published: (2025)
ST-Tree with Interpretability for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
Interpretable Time Series Models for Wastewater Modeling in Combined Sewer Overflows
by: Chiaburu, Teodor, et al.
Published: (2024)
by: Chiaburu, Teodor, et al.
Published: (2024)
Inherently Interpretable Time Series Classification via Multiple Instance Learning
by: Early, Joseph, et al.
Published: (2023)
by: Early, Joseph, et al.
Published: (2023)
Benchmarking Counterfactual Interpretability in Deep Learning Models for Time Series Classification
by: Kan, Ziwen, et al.
Published: (2024)
by: Kan, Ziwen, et al.
Published: (2024)
Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms
by: Farahani, Mojtaba A., et al.
Published: (2023)
by: Farahani, Mojtaba A., et al.
Published: (2023)
EVIL: Evolving Interpretable Algorithms for Zero-Shot Inference on Event Sequences and Time Series with LLMs
by: Berghaus, David
Published: (2026)
by: Berghaus, David
Published: (2026)
PHEATPRUNER: Interpretable Data-centric Feature Selection for Multivariate Time Series Classification through Persistent Homology
by: Pham, Anh-Duy, et al.
Published: (2025)
by: Pham, Anh-Duy, et al.
Published: (2025)
Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series
by: Song, Xianhao, et al.
Published: (2026)
by: Song, Xianhao, et al.
Published: (2026)
Interpretable Time Series Autoregression for Periodicity Quantification
by: Chen, Xinyu, et al.
Published: (2025)
by: Chen, Xinyu, et al.
Published: (2025)
Correlating Time Series with Interpretable Convolutional Kernels
by: Chen, Xinyu, et al.
Published: (2024)
by: Chen, Xinyu, et al.
Published: (2024)
Semi-Periodic Activation for Time Series Classification
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
by: Júnior, José Gilberto Barbosa de Medeiros, et al.
Published: (2024)
What-If Explanations Over Time: Counterfactuals for Time Series Classification
by: Schlegel, Udo, et al.
Published: (2026)
by: Schlegel, Udo, et al.
Published: (2026)
Evaluating Time Series Models for Urban Wastewater Management: Predictive Performance, Model Complexity and Resilience
by: Singh, Vipin, et al.
Published: (2025)
by: Singh, Vipin, et al.
Published: (2025)
Explanation Space: A New Perspective into Time Series Interpretability
by: Rezaei, Shahbaz, et al.
Published: (2024)
by: Rezaei, Shahbaz, et al.
Published: (2024)
Interpreting Outliers in Time Series Data through Decoding Autoencoder
by: Knab, Patrick, et al.
Published: (2024)
by: Knab, Patrick, et al.
Published: (2024)
PatchDecomp: Interpretable Patch-Based Time Series Forecasting
by: Tomioka, Hiroki, et al.
Published: (2026)
by: Tomioka, Hiroki, et al.
Published: (2026)
Diffusion-TS: Interpretable Diffusion for General Time Series Generation
by: Yuan, Xinyu, et al.
Published: (2024)
by: Yuan, Xinyu, et al.
Published: (2024)
Utilizing Data Fingerprints for Privacy-Preserving Algorithm Selection in Time Series Classification: Performance and Uncertainty Estimation on Unseen Datasets
by: Böcking, Lars, et al.
Published: (2024)
by: Böcking, Lars, et al.
Published: (2024)
CAFO: Feature-Centric Explanation on Time Series Classification
by: Kim, Jaeho, et al.
Published: (2024)
by: Kim, Jaeho, et al.
Published: (2024)
iTFKAN: Interpretable Time Series Forecasting with Kolmogorov-Arnold Network
by: Liang, Ziran, et al.
Published: (2025)
by: Liang, Ziran, et al.
Published: (2025)
Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
by: Cho, Dongchan, et al.
Published: (2025)
by: Cho, Dongchan, et al.
Published: (2025)
Kolmogorov-Arnold Networks for Time Series: Bridging Predictive Power and Interpretability
by: Xu, Kunpeng, et al.
Published: (2024)
by: Xu, Kunpeng, et al.
Published: (2024)
EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
by: Chakraborty, Sanjay, et al.
Published: (2024)
by: Chakraborty, Sanjay, et al.
Published: (2024)
Bridging Neural Networks and Dynamic Time Warping for Adaptive Time Series Classification
by: Qu, Jintao, et al.
Published: (2025)
by: Qu, Jintao, et al.
Published: (2025)
A Unified Contrastive-Generative Framework for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2025)
by: Liu, Ziyu, et al.
Published: (2025)
Leveraging Generic Time Series Foundation Models for EEG Classification
by: Gnassounou, Théo, et al.
Published: (2025)
by: Gnassounou, Théo, et al.
Published: (2025)
CATS: Mitigating Correlation Shift for Multivariate Time Series Classification
by: Lin, Xiao, et al.
Published: (2025)
by: Lin, Xiao, et al.
Published: (2025)
Gradient-based Model Shortcut Detection for Time Series Classification
by: Ibarra, Salomon, et al.
Published: (2025)
by: Ibarra, Salomon, et al.
Published: (2025)
Meta-learning to Address Data Shift in Time Series Classification
by: Myren, Samuel, et al.
Published: (2026)
by: Myren, Samuel, et al.
Published: (2026)
Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting
by: Green, Riku, et al.
Published: (2024)
by: Green, Riku, et al.
Published: (2024)
Bridging Classification and Reconstruction: Cooperative Time Series Anomaly Detection
by: Tang, Qideng, et al.
Published: (2026)
by: Tang, Qideng, et al.
Published: (2026)
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
by: Le, Xuan-May, et al.
Published: (2024)
by: Le, Xuan-May, et al.
Published: (2024)
Explaining Time Series Classification Predictions via Causal Attributions
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)
Guidelines for Augmentation Selection in Contrastive Learning for Time Series Classification
by: Liu, Ziyu, et al.
Published: (2024)
by: Liu, Ziyu, et al.
Published: (2024)
Similar Items
-
On a Combinatorial Problem Arising in Machine Teaching
by: Håvardstun, Brigt, et al.
Published: (2024) -
Teaching and Learning under Deductive Errors
by: Telle, Jan Arne, et al.
Published: (2026) -
When Redundancy Matters: Machine Teaching of Representations
by: Ferri, Cèsar, et al.
Published: (2024) -
Relative Drawing Identification Complexity is Invariant to Modality in Vision-Language Models
by: Freitas, Diogo, et al.
Published: (2025) -
CRITS: Convolutional Rectifier for Interpretable Time Series Classification
by: Kuratomi, Alejandro, et al.
Published: (2025)