Saved in:
| Main Authors: | Mekonnen, Ephrem Tibebe, Longo, Luca, Rizzo, Lucas, Dondio, Pierpaolo |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.13065 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest
by: Ceschin, Matteo, et al.
Published: (2025)
by: Ceschin, Matteo, et al.
Published: (2025)
What-If Explanations Over Time: Counterfactuals for Time Series Classification
by: Schlegel, Udo, et al.
Published: (2026)
by: Schlegel, Udo, et al.
Published: (2026)
TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
Regional Explanations: Bridging Local and Global Variable Importance
by: Amoukou, Salim I., et al.
Published: (2026)
by: Amoukou, Salim I., et al.
Published: (2026)
GLEAMS: Bridging the Gap Between Local and Global Explanations
by: Visani, Giorgio, et al.
Published: (2024)
by: Visani, Giorgio, et al.
Published: (2024)
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies
by: Der, Audrey, et al.
Published: (2024)
by: Der, Audrey, 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)
Explanation Space: A New Perspective into Time Series Interpretability
by: Rezaei, Shahbaz, et al.
Published: (2024)
by: Rezaei, Shahbaz, et al.
Published: (2024)
TIMING: Temporality-Aware Integrated Gradients for Time Series Explanation
by: Jang, Hyeongwon, et al.
Published: (2025)
by: Jang, Hyeongwon, et al.
Published: (2025)
Time-Transformer: Integrating Local and Global Features for Better Time Series Generation (Extended Version)
by: Liu, Yuansan, et al.
Published: (2023)
by: Liu, Yuansan, et al.
Published: (2023)
The GECo algorithm for Graph Neural Networks Explanation
by: Calderaro, Salvatore, et al.
Published: (2024)
by: Calderaro, Salvatore, et al.
Published: (2024)
SSET: Swapping-Sliding Explanation for Time Series Classifiers in Affect Detection
by: Fouladgar, Nazanin, et al.
Published: (2024)
by: Fouladgar, Nazanin, et al.
Published: (2024)
Interpretable AI for Time-Series: Multi-Model Heatmap Fusion with Global Attention and NLP-Generated Explanations
by: Francis, Jiztom Kavalakkatt, et al.
Published: (2025)
by: Francis, Jiztom Kavalakkatt, et al.
Published: (2025)
Global and Local Topology-Aware Attention with Persistent Homology and Euler Biases for Time-Series Forecasting
by: Faghihi, Usef, et al.
Published: (2026)
by: Faghihi, Usef, et al.
Published: (2026)
CORTEX: A Cost-Sensitive Rule and Tree Extraction Method
by: Kopanja, Marija, et al.
Published: (2025)
by: Kopanja, Marija, et al.
Published: (2025)
TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation
by: Ma, Hongnan, et al.
Published: (2025)
by: Ma, Hongnan, et al.
Published: (2025)
ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
by: Huang, Bosong, et al.
Published: (2025)
by: Huang, Bosong, et al.
Published: (2025)
Locally-Minimal Probabilistic Explanations
by: Izza, Yacine, et al.
Published: (2023)
by: Izza, Yacine, et al.
Published: (2023)
Unifying Perspectives: Plausible Counterfactual Explanations on Global, Group-wise, and Local Levels
by: Furman, Oleksii, et al.
Published: (2024)
by: Furman, Oleksii, et al.
Published: (2024)
M-CELS: Counterfactual Explanation for Multivariate Time Series Data Guided by Learned Saliency Maps
by: Li, Peiyu, et al.
Published: (2024)
by: Li, Peiyu, et al.
Published: (2024)
On the Regularization of Learnable Embeddings for Time Series Forecasting
by: Butera, Luca, et al.
Published: (2024)
by: Butera, Luca, et al.
Published: (2024)
STEP: Learning STructured Embeddings for Progressive Time Series
by: Thil, Lucas, et al.
Published: (2026)
by: Thil, Lucas, et al.
Published: (2026)
ConformaDecompose: Explaining Uncertainty via Calibration Localization
by: Yapicioglu, Fatima Rabia, et al.
Published: (2026)
by: Yapicioglu, Fatima Rabia, et al.
Published: (2026)
Global Concept Explanations for Graphs by Contrastive Learning
by: Teufel, Jonas, et al.
Published: (2024)
by: Teufel, Jonas, et al.
Published: (2024)
Enhancing Multivariate Time Series Forecasting with Global Temporal Retrieval
by: Cao, Fanpu, et al.
Published: (2026)
by: Cao, Fanpu, et al.
Published: (2026)
No Single Metric Tells the Whole Story: A Multi-Dimensional Evaluation Framework for Uncertainty Attributions
by: Schiller, Emily, et al.
Published: (2026)
by: Schiller, Emily, et al.
Published: (2026)
On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating
by: Widener, Michael, et al.
Published: (2025)
by: Widener, Michael, et al.
Published: (2025)
From Prototypes to Sparse ECG Explanations: SHAP-Driven Counterfactuals for Multivariate Time-Series Multi-class Classification
by: Mozolewski, Maciej, et al.
Published: (2025)
by: Mozolewski, Maciej, et al.
Published: (2025)
Explaining Time Series via Contrastive and Locally Sparse Perturbations
by: Liu, Zichuan, et al.
Published: (2024)
by: Liu, Zichuan, et al.
Published: (2024)
Diffusion-based Time Series Forecasting for Sewerage Systems
by: Pearson, Nicholas A., et al.
Published: (2025)
by: Pearson, Nicholas A., et al.
Published: (2025)
Rigorous Probabilistic Guarantees for Robust Counterfactual Explanations
by: Marzari, Luca, et al.
Published: (2024)
by: Marzari, Luca, et al.
Published: (2024)
MEGAN: Multi-Explanation Graph Attention Network
by: Teufel, Jonas, et al.
Published: (2022)
by: Teufel, Jonas, et al.
Published: (2022)
Explanation Multiplicity in SHAP: Characterization and Assessment
by: Hwang, Hyunseung, et al.
Published: (2026)
by: Hwang, Hyunseung, et al.
Published: (2026)
Why Do Time Series Models Need Long Context Windows?
by: Butera, Luca, et al.
Published: (2026)
by: Butera, Luca, et al.
Published: (2026)
Causality-Aware Local Interpretable Model-Agnostic Explanations
by: Cinquini, Martina, et al.
Published: (2022)
by: Cinquini, Martina, et al.
Published: (2022)
RobustX: Robust Counterfactual Explanations Made Easy
by: Jiang, Junqi, et al.
Published: (2025)
by: Jiang, Junqi, et al.
Published: (2025)
GALACTIC: Global and Local Agnostic Counterfactuals for Time-series Clustering
by: Fragkathoulas, Christos, et al.
Published: (2026)
by: Fragkathoulas, Christos, et al.
Published: (2026)
Global Feature Enhancing and Fusion Framework for Strain Gauge Time Series Classification
by: Zhang, Xu, et al.
Published: (2025)
by: Zhang, Xu, et al.
Published: (2025)
Global Cross-Time Attention Fusion for Enhanced Solar Flare Prediction from Multivariate Time Series
by: Vural, Onur, et al.
Published: (2025)
by: Vural, Onur, et al.
Published: (2025)
From Similarity to Superiority: Channel Clustering for Time Series Forecasting
by: Chen, Jialin, et al.
Published: (2024)
by: Chen, Jialin, et al.
Published: (2024)
Similar Items
-
Extending Decision Predicate Graphs for Comprehensive Explanation of Isolation Forest
by: Ceschin, Matteo, et al.
Published: (2025) -
What-If Explanations Over Time: Counterfactuals for Time Series Classification
by: Schlegel, Udo, et al.
Published: (2026) -
TimeX++: Learning Time-Series Explanations with Information Bottleneck
by: Liu, Zichuan, et al.
Published: (2024) -
Regional Explanations: Bridging Local and Global Variable Importance
by: Amoukou, Salim I., et al.
Published: (2026) -
GLEAMS: Bridging the Gap Between Local and Global Explanations
by: Visani, Giorgio, et al.
Published: (2024)