PHEATPRUNER: Interpretable Data-centric Feature Selection for Multivariate Time Series Classification through Persistent Homology
Fuente:
arXiv
Saved in:
| Main Authors: | Pham, Anh-Duy, Kashongwe, Olivier Basole, Atzmueller, Martin, Römer, Tim |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Knowledge-Augmented Explainable and Interpretable Learning for Anomaly Detection and Diagnosis
by: Atzmueller, Martin, et al.
Published: (2024)
by: Atzmueller, Martin, et al.
Published: (2024)
ST-Tree with Interpretability for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
Review of Data-centric Time Series Analysis from Sample, Feature, and Period
by: Sun, Chenxi, et al.
Published: (2024)
by: Sun, Chenxi, et al.
Published: (2024)
Persistent Homology-induced Graph Ensembles for Time Series Regressions
by: Nguyen, Viet The, et al.
Published: (2025)
by: Nguyen, Viet The, et al.
Published: (2025)
Saliency Map-Guided Knowledge Discovery for Subclass Identification with LLM-Based Symbolic Approximations
by: Bohne, Tim, et al.
Published: (2025)
by: Bohne, Tim, et al.
Published: (2025)
Exploring Large Language Models for Feature Selection: A Data-centric Perspective
by: Li, Dawei, et al.
Published: (2024)
by: Li, Dawei, et al.
Published: (2024)
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)
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)
PRISM: Lightweight Multivariate Time-Series Classification through Symmetric Multi-Resolution Convolutional Layers
by: Zucchi, Federico, et al.
Published: (2025)
by: Zucchi, Federico, 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)
ShapeFormer: Shapelet Transformer for Multivariate Time Series Classification
by: Le, Xuan-May, et al.
Published: (2024)
by: Le, Xuan-May, et al.
Published: (2024)
Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
by: Cho, Dongchan, et al.
Published: (2025)
by: Cho, Dongchan, et al.
Published: (2025)
EDformer: Embedded Decomposition Transformer for Interpretable Multivariate Time Series Predictions
by: Chakraborty, Sanjay, et al.
Published: (2024)
by: Chakraborty, Sanjay, 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)
Clustering-based Anomaly Detection in Multivariate Time Series Data
by: Li, Jinbo, et al.
Published: (2025)
by: Li, Jinbo, et al.
Published: (2025)
Fun-TSG: A Function-Driven Multivariate Time Series Generator with Variable-Level Anomaly Labeling
by: Lotte, Pierre, et al.
Published: (2026)
by: Lotte, Pierre, et al.
Published: (2026)
Explainable and Interpretable Forecasts on Non-Smooth Multivariate Time Series for Responsible Gameplay
by: Jagirdar, Hussain, et al.
Published: (2025)
by: Jagirdar, Hussain, et al.
Published: (2025)
Evaluating Simplification Algorithms for Interpretability of Time Series Classification
by: Håvardstun, Brigt, et al.
Published: (2025)
by: Håvardstun, Brigt, 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)
TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
by: Taga, Ege Onur, et al.
Published: (2025)
by: Taga, Ege Onur, et al.
Published: (2025)
Causal and Local Correlations Based Network for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
Exploring Spiking Neural Networks for Binary Classification in Multivariate Time Series at the Edge
by: Ghawaly, James, et al.
Published: (2025)
by: Ghawaly, James, et al.
Published: (2025)
Comprehensive Evaluation of Prototype Neural Networks
by: Schlinge, Philipp, et al.
Published: (2025)
by: Schlinge, Philipp, et al.
Published: (2025)
CAFO: Feature-Centric Explanation on Time Series Classification
by: Kim, Jaeho, et al.
Published: (2024)
by: Kim, Jaeho, et al.
Published: (2024)
Contrast Similarity-Aware Dual-Pathway Mamba for Multivariate Time Series Node Classification
by: Du, Mingsen, et al.
Published: (2024)
by: Du, Mingsen, et al.
Published: (2024)
One-Step Graph-Structured Neural Flows for Irregular Multivariate Time Series Classification
by: Gao, Mengzhou, et al.
Published: (2026)
by: Gao, Mengzhou, et al.
Published: (2026)
POCKET: Pruning Random Convolution Kernels for Time Series Classification from a Feature Selection Perspective
by: Chen, Shaowu, et al.
Published: (2023)
by: Chen, Shaowu, et al.
Published: (2023)
Temporal Gaussian Copula For Clinical Multivariate Time Series Data Imputation
by: Su, Ye, et al.
Published: (2025)
by: Su, Ye, et al.
Published: (2025)
mTSBench: Benchmarking Multivariate Time Series Anomaly Detection and Model Selection at Scale
by: Zhou, Xiaona, et al.
Published: (2025)
by: Zhou, Xiaona, et al.
Published: (2025)
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)
Early Detection of Multidrug Resistance Using Multivariate Time Series Analysis and Interpretable Patient-Similarity Representations
by: Escudero-Arnanz, Óscar, et al.
Published: (2025)
by: Escudero-Arnanz, Óscar, et al.
Published: (2025)
Integrating Prior Observations for Incremental 3D Scene Graph Prediction
by: Renz, Marian, et al.
Published: (2025)
by: Renz, Marian, et al.
Published: (2025)
Revisiting Attention for Multivariate Time Series Forecasting
by: Wu, Haixiang
Published: (2024)
by: Wu, Haixiang
Published: (2024)
Are KANs Effective for Multivariate Time Series Forecasting?
by: Han, Xiao, et al.
Published: (2024)
by: Han, Xiao, et al.
Published: (2024)
Nearest Neighbor Multivariate Time Series Forecasting
by: Zhang, Huiliang, et al.
Published: (2025)
by: Zhang, Huiliang, et al.
Published: (2025)
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)
Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series
by: Zerkouk, Meriem, et al.
Published: (2025)
by: Zerkouk, Meriem, et al.
Published: (2025)
DisMS-TS: Eliminating Redundant Multi-Scale Features for Time Series Classification
by: Liu, Zhipeng, et al.
Published: (2025)
by: Liu, Zhipeng, et al.
Published: (2025)
Similar Items
-
Knowledge-Augmented Explainable and Interpretable Learning for Anomaly Detection and Diagnosis
by: Atzmueller, Martin, et al.
Published: (2024) -
ST-Tree with Interpretability for Multivariate Time Series Classification
by: Du, Mingsen, et al.
Published: (2024) -
Review of Data-centric Time Series Analysis from Sample, Feature, and Period
by: Sun, Chenxi, et al.
Published: (2024) -
Persistent Homology-induced Graph Ensembles for Time Series Regressions
by: Nguyen, Viet The, et al.
Published: (2025) -
Saliency Map-Guided Knowledge Discovery for Subclass Identification with LLM-Based Symbolic Approximations
by: Bohne, Tim, et al.
Published: (2025)