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The UCR time series archive
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-32391-0_111openalex-snapshot
Finding The Clustering Consensus of Time Series with Multi-Scale Transform
inferredcites →https://doi.org/10.1007/3-540-44466-1_35openalex-snapshot
AIM: Approximate Intelligent Matching for Time Series Data
inferredcites →https://doi.org/10.1007/3-540-57301-1_5openalex-snapshot
Efficient similarity search in sequence databases
inferredcites →https://doi.org/10.1007/978-1-4612-4380-9_16openalex-snapshot
Individual Comparisons by Ranking Methods
inferredcites →https://doi.org/10.1007/bf01250288openalex-snapshot
Local discriminant bases and their applications
inferredcites →https://doi.org/10.1007/pl00011669openalex-snapshot
Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases
inferredcites →https://doi.org/10.1007/s10618-013-0312-3openalex-snapshot
CID: an efficient complexity-invariant distance for time series
inferredcites →https://doi.org/10.1007/s10618-013-0322-1openalex-snapshot
Classification of time series by shapelet transformation
inferredcites →https://doi.org/10.1007/s10618-014-0377-7openalex-snapshot
The BOSS is concerned with time series classification in the presence of noise
inferredcites →https://doi.org/10.1007/s10618-015-0415-0openalex-snapshot
Classification of streaming time series under more realistic assumptions
inferredcites →https://doi.org/10.1007/s10618-016-0483-9openalex-snapshot
The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances
inferredcites →https://doi.org/10.1007/s10618-018-0565-yopenalex-snapshot
Optimizing dynamic time warping’s window width for time series data mining applications
inferredcites →https://doi.org/10.1023/a:1009752403260openalex-snapshot
On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach
inferredcites →https://doi.org/10.1023/a:1024988512476openalex-snapshot
On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
inferredcites →https://doi.org/10.1080/00401706.1999.10485954openalex-snapshot
Nonparametric Statistical Methods
inferredcites →https://doi.org/10.1080/01621459.1937.10503522openalex-snapshot
The Use of Ranks to Avoid the Assumption of Normality Implicit in the Analysis of Variance
inferredcites →https://doi.org/10.1109/aiccsa.2017.29openalex-snapshot
SAX-Based Representation with Longest Common Subsequence Dissimilarity Measure for Time Series Data Classification
inferredcites →https://doi.org/10.1109/bigdata.2017.8258009openalex-snapshot
Judicious setting of Dynamic Time Warping's window width allows more accurate classification of time series
inferredcites →https://doi.org/10.1109/icdm.2016.0133openalex-snapshot
HIVE-COTE: The Hierarchical Vote Collective of Transformation-Based Ensembles for Time Series Classification
inferredcites →https://doi.org/10.1109/icdm.2016.0161openalex-snapshot
Prefix and Suffix Invariant Dynamic Time Warping
inferredcites →https://doi.org/10.1109/icdm.2017.106openalex-snapshot
Generating Synthetic Time Series to Augment Sparse Datasets
inferredcites →https://doi.org/10.1109/icdm.2018.00119openalex-snapshot
Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios
inferredcites →https://doi.org/10.1109/icpr.2010.764openalex-snapshot
The Balanced Accuracy and Its Posterior Distribution
inferredcites →https://doi.org/10.1111/j.1469-1809.1936.tb02137.xopenalex-snapshot
THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS
inferredcites →https://doi.org/10.1142/s0218194016400088openalex-snapshot
Time Series Classification with Discrete Wavelet Transformed Data
inferredcites →https://doi.org/10.1145/2851613.2851891openalex-snapshot
A new time series classification approach based on recurrence quantification analysis and Gabor filter
inferredcites →https://doi.org/10.1145/312129.318357openalex-snapshot
Adaptive query processing for time-series data
inferredcites →https://doi.org/10.1145/3154862.3154927openalex-snapshot
Gesture recognition using symbolic aggregate approximation and dynamic time warping on motion data
inferredcites →https://doi.org/10.1145/3182382openalex-snapshot
Time Series Classification with HIVE-COTE
inferredcites →https://doi.org/10.1145/3317287.3328534openalex-snapshot
Troubling Trends in Machine Learning Scholarship
inferredcites →https://doi.org/10.1184/r1/28996229openalex-snapshot
Robust Learning with Highly Skewed Category Distributions
inferredcites →https://doi.org/10.1214/aoms/1177731944openalex-snapshot
A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
inferredcites →https://doi.org/10.1371/journal.pone.0173320openalex-snapshot
Dynamic time warping assessment of high-resolution melt curves provides a robust metric for fungal identification
inferredcites →https://doi.org/10.18293/seke2016-067openalex-snapshot
Time Series Classification with Discrete Wavelet Transformed Data: Insights from an Empirical Study
inferredcites →https://doi.org/10.20965/jaciii.2006.p0069openalex-snapshot
Combining the Global and Partial Information for Distance-Based Time Series Classification and Clustering
inferredcites →https://doi.org/10.2307/3498751openalex-snapshot
Nonparametric Statistics for the Behavioral Sciences
inferredcites →https://doi.org/10.2307/4615733openalex-snapshot
A Simple Sequentially Rejective Multiple Test Procedure
inferredcites →https://doi.org/10.4172/2155-6180.1000132openalex-snapshot
Evaluating Measures of Indicators of Diagnostic Test Performance: Fundamental Meanings and Formulars
inferredcites →https://doi.org/10.48550/arxiv.1505.02288openalex-snapshot
Should we really use post-hoc tests based on mean-ranks?
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4790011openalex-extracted
A Structural Anomaly Detection Method Based on Fusion Interval Representation of Multi-Grained Morphological Information
inferred← citeshttps://doi.org/10.2139/ssrn.4829471openalex-extracted
A Recurrence Plot-Based Graph Convolutional Network for Time Series Classification
inferred← citeshttps://doi.org/10.1002/9781119417408.ch5openalex-snapshot
CLUSTERING AND CLASSIFICATION OF TIME SERIES
inferred← citeshttps://doi.org/10.1002/9781394178445.ch9openalex-snapshot
Evolutionary Large‐Scale Multi‐Objective Optimization in Deep Learning
inferred← citeshttps://doi.org/10.1002/cjs.70053openalex-snapshot
A multi‐label classification approach for functional data based on conformal prediction bands
inferred← citeshttps://doi.org/10.1002/cpe.7331openalex-snapshot
Time series data augmentation method of small sample based on optimized generative adversarial network
inferred← citeshttps://doi.org/10.1002/cpe.8034openalex-snapshot
AE‐Integrated : Real‐time network intrusion detection with Apache Kafka and autoencoder
inferred← citeshttps://doi.org/10.1002/cpe.8395openalex-snapshot
A Distributed Information Granulation Method for Time Series Clustering
inferred← citeshttps://doi.org/10.1002/ece3.10520openalex-snapshot
A user‐friendly guide to using distance measures to compare time series in ecology
inferred← citeshttps://doi.org/10.1002/eng2.12739openalex-snapshot
Financial time series classification method based on low‐frequency approximate representation
inferred← citeshttps://doi.org/10.1002/gdj3.281openalex-snapshot
Time‐domain spectra of ultrasonic wave transmitted through granite and gypsum samples containing artificial defects
inferred← citeshttps://doi.org/10.1002/pen.70407openalex-snapshot
Real‐Time Diagnosis of Polymer Compositions During Extrusion via Pressure Signals and Machine Learning
inferred← citeshttps://doi.org/10.1002/sta4.712openalex-snapshot
New two‐sample test utilizing interpoint distance discrepancy
inferred← citeshttps://doi.org/10.1002/widm.1491openalex-snapshot
A geometric framework for outlier detection in high‐dimensional data
inferred← citeshttps://doi.org/10.1002/widm.70058openalex-snapshot
Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them
inferred← citeshttps://doi.org/10.1007/978-1-0716-0826-5_2openalex-snapshot
Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning
inferred← citeshttps://doi.org/10.1007/978-3-030-33607-3_16openalex-snapshot
A Hybrid Approach to Time Series Classification with Shapelets
inferred← citeshttps://doi.org/10.1007/978-3-030-33607-3_2openalex-snapshot
Scalable Dictionary Classifiers for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-36708-4_23openalex-snapshot
On the Initialization of Long Short-Term Memory Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-50153-2_43openalex-snapshot
Fuzzy k-NN Based Classifiers for Time Series with Soft Labels
inferred← citeshttps://doi.org/10.1007/978-3-030-55130-8_41openalex-snapshot
Extracting Distinctive Shapelets with Random Selection for Early Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-57802-2_14openalex-snapshot
On the Performance of Deep Learning Models for Time Series Classification in Streaming
inferred← citeshttps://doi.org/10.1007/978-3-030-58930-1_26openalex-snapshot
One-Class Subject Authentication Using Feature Extraction by Grammatical Evolution on Accelerometer Data
inferred← citeshttps://doi.org/10.1007/978-3-030-59410-7_50openalex-snapshot
Enhancing Linear Time Complexity Time Series Classification with Hybrid Bag-Of-Patterns
inferred← citeshttps://doi.org/10.1007/978-3-030-61380-8_29openalex-snapshot
Towards an Instance-Level Meta-learning-Based Ensemble for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-63089-8_27openalex-snapshot
Qute: Query by Text Search for Time Series Data
inferred← citeshttps://doi.org/10.1007/978-3-030-64243-3_10openalex-snapshot
An Improved Sparse Representation Classifier Based on Data Augmentation for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-65742-0_1openalex-snapshot
On the Usage and Performance of the Hierarchical Vote Collective of Transformation-Based Ensembles Version 1.0 (HIVE-COTE v1.0)
inferred← citeshttps://doi.org/10.1007/978-3-030-65867-0_12openalex-snapshot
Large Astronomical Time Series Pre-processing for Classification Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-67658-2_38openalex-snapshot
The Temporal Dictionary Ensemble (TDE) Classifier for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-68796-0_2openalex-snapshot
Post-hoc Explanation Options for XAI in Deep Learning: The Insight Centre for Data Analytics Perspective
inferred← citeshttps://doi.org/10.1007/978-3-030-75381-8_48openalex-snapshot
Investigation of Machine Learning Models for a Time Series Classification Task in Radial–Axial Ring Rolling
inferred← citeshttps://doi.org/10.1007/978-3-030-79463-7_51openalex-snapshot
Target Class Supervised Sample Length and Training Sample Reduction of Univariate Time Series
inferred← citeshttps://doi.org/10.1007/978-3-030-86475-0_23openalex-snapshot
TSX-Means: An Optimal K Search Approach for Time Series Clustering
inferred← citeshttps://doi.org/10.1007/978-3-030-86957-1_3openalex-snapshot
Instance-Based Counterfactual Explanations for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-030-87869-6_56openalex-snapshot
Multivariate Adaptive Downsampling Algorithm for Industry 4.0 Data Visualization
inferred← citeshttps://doi.org/10.1007/978-3-030-89880-9_9openalex-snapshot
Testing Time Series Classification of UCR Archive Signals Using Feature to Image Transformation (FIT) Algorithm
inferred← citeshttps://doi.org/10.1007/978-3-031-00126-0_39openalex-snapshot
Efficient Consensus Motif Discovery of All Lengths in Multiple Time Series
inferred← citeshttps://doi.org/10.1007/978-3-031-05933-9_38openalex-snapshot
Smooth Perturbations for Time Series Adversarial Attacks
inferred← citeshttps://doi.org/10.1007/978-3-031-05936-0_28openalex-snapshot
Open Set Recognition for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-07689-3_18openalex-snapshot
Transfer Learning for Time Series Classification Using Synthetic Data Generation
inferred← citeshttps://doi.org/10.1007/978-3-031-09034-9_19openalex-snapshot
Similarity Forest for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-09037-0_53openalex-snapshot
Random Dilated Shapelet Transform: A New Approach for Time Series Shapelets
inferred← citeshttps://doi.org/10.1007/978-3-031-09282-4_13openalex-snapshot
The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier
inferred← citeshttps://doi.org/10.1007/978-3-031-09282-4_19openalex-snapshot
TS-QUAD: A Smaller Elastic Ensemble for Time Series Classification with No Reduction in Accuracy
inferred← citeshttps://doi.org/10.1007/978-3-031-12670-3_14openalex-snapshot
Outlier/Anomaly Detection of Univariate Time Series: A Dataset Collection and Benchmark
inferred← citeshttps://doi.org/10.1007/978-3-031-12766-3_6openalex-snapshot
The Performance of a Combined Distance Between Time Series
inferred← citeshttps://doi.org/10.1007/978-3-031-24378-3_6openalex-snapshot
Window Size Selection in Unsupervised Time Series Analytics: A Review and Benchmark
inferred← citeshttps://doi.org/10.1007/978-3-031-24378-3_8openalex-snapshot
Data Augmentation for Time Series Classification with Deep Learning Models
inferred← citeshttps://doi.org/10.1007/978-3-031-24378-3_9openalex-snapshot
Dimension Selection Strategies for Multivariate Time Series Classification with HIVE-COTEv2.0
inferred← citeshttps://doi.org/10.1007/978-3-031-25891-6_24openalex-snapshot
Normalization in Motif Discovery
inferred← citeshttps://doi.org/10.1007/978-3-031-26387-3_3openalex-snapshot
Structured Nonlinear Discriminant Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-26422-1_1openalex-snapshot
Few-Shot Forecasting of Time-Series with Heterogeneous Channels
inferred← citeshttps://doi.org/10.1007/978-3-031-26422-1_6openalex-snapshot
TS-MIoU: A Time Series Similarity Metric Without Mapping
inferred← citeshttps://doi.org/10.1007/978-3-031-27077-2_27openalex-snapshot
Music Instrument Classification Reprogrammed
inferred← citeshttps://doi.org/10.1007/978-3-031-30047-9_33openalex-snapshot
ROCKAD: Transferring ROCKET to Whole Time Series Anomaly Detection
inferred← citeshttps://doi.org/10.1007/978-3-031-30105-6_46openalex-snapshot
Auxiliary Network: Scalable and Agile Online Learning for Dynamic System with Inconsistently Available Inputs
inferred← citeshttps://doi.org/10.1007/978-3-031-30111-7_18openalex-snapshot
Universal Distributional Decision-Based Black-Box Adversarial Attack with Reinforcement Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-30191-9_3openalex-snapshot
Unsupervised Attack Isolation in Cyber-physical Systems: A Competitive Test of Clustering Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-031-30637-2_10openalex-snapshot
Long-Tailed Time Series Classification via Feature Space Rebalancing
inferred← citeshttps://doi.org/10.1007/978-3-031-30637-2_15openalex-snapshot
GP-HLS: Gaussian Process-Based Unsupervised High-Level Semantics Representation Learning of Multivariate Time Series
inferred← citeshttps://doi.org/10.1007/978-3-031-35415-1_10openalex-snapshot
Auto-TSA: An Automatic Time Series Analysis System Based on Meta-learning
inferred← citeshttps://doi.org/10.1007/978-3-031-37731-0_16openalex-snapshot
Motif-Guided Time Series Counterfactual Explanations
inferred← citeshttps://doi.org/10.1007/978-3-031-41774-0_58openalex-snapshot
Overview of Time Series Classification Based on Symbolic Discretization for ECG Applications
inferred← citeshttps://doi.org/10.1007/978-3-031-42536-3_26openalex-snapshot
Enhancing Time Series Anomaly Detection Using Discretization and Word Embeddings
inferred← citeshttps://doi.org/10.1007/978-3-031-44070-0_8openalex-snapshot
State Graph Based Explanation Approach for Black-Box Time Series Model
inferred← citeshttps://doi.org/10.1007/978-3-031-44070-0_9openalex-snapshot
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAI
inferred← citeshttps://doi.org/10.1007/978-3-031-44223-0_19openalex-snapshot
MIPCE: Generating Multiple Patches Counterfactual-Changing Explanations for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-45933-7_25openalex-snapshot
Two-Stage Anomaly Detection in LEO Satellite Network
inferred← citeshttps://doi.org/10.1007/978-3-031-49896-1_14openalex-snapshot
Back to Basics: A Sanity Check on Modern Time Series Classification Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-031-49896-1_4openalex-snapshot
Clustering Time Series with k-Medoids Based Algorithms
inferred← citeshttps://doi.org/10.1007/978-3-031-49896-1_8openalex-snapshot
Extracting Features from Random Subseries: A Hybrid Pipeline for Time Series Classification and Extrinsic Regression
inferred← citeshttps://doi.org/10.1007/978-3-031-49896-1_9openalex-snapshot
ShapeDBA: Generating Effective Time Series Prototypes Using ShapeDTW Barycenter Averaging
inferred← citeshttps://doi.org/10.1007/978-3-031-51643-6_28openalex-snapshot
XAI for Time-Series Classification Leveraging Image Highlight Methods
inferred← citeshttps://doi.org/10.1007/978-3-031-70359-1_11openalex-snapshot
Improving the Evaluation and Actionability of Explanation Methods for Multivariate Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-72347-6_16openalex-snapshot
Fusion of Image Representations for Time Series Classification with Deep Learning
inferred← citeshttps://doi.org/10.1007/978-3-031-74633-8_1openalex-snapshot
Introducing the Attribution Stability Indicator: A Measure for Time Series XAI Attributions
inferred← citeshttps://doi.org/10.1007/978-3-031-77066-1_5openalex-snapshot
Highly Scalable Time Series Classification for Very Large Datasets
inferred← citeshttps://doi.org/10.1007/978-3-031-77066-1_6openalex-snapshot
Classification of Raw MEG/EEG Data with Detach-Rocket Ensemble: An Improved ROCKET Algorithm for Multivariate Time Series Analysis
inferred← citeshttps://doi.org/10.1007/978-3-031-77527-7_2openalex-snapshot
Time Series and Similarity Measures
inferred← citeshttps://doi.org/10.1007/978-3-031-77527-7_3openalex-snapshot
Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-77527-7_4openalex-snapshot
The Impact of Global Constraints on the Accuracy of Elastic Similarity Measures
inferred← citeshttps://doi.org/10.1007/978-3-031-77527-7_5openalex-snapshot
The Influence of Weighting Schemes on Classification Accuracy
inferred← citeshttps://doi.org/10.1007/978-3-031-77527-7_6openalex-snapshot
Combined Influence of Weighting Schemes and Global Constraints on Classification Accuracy
inferred← citeshttps://doi.org/10.1007/978-3-031-78107-0_14openalex-snapshot
Capturing Temporal Components for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-78395-1_26openalex-snapshot
TS-NUC : Nearest Unlike Cluster Guided Generative Counterfactual Estimation for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-80507-3_19openalex-snapshot
An Interesting Property of Random Forest Distances with Respect to the Curse of Dimensionality
inferred← citeshttps://doi.org/10.1007/978-3-031-93631-9_4openalex-snapshot
When is Reservoir Computing with Cellular Automata Beneficial?
inferred← citeshttps://doi.org/10.1007/978-3-032-00624-0_13openalex-snapshot
AARC-FE: Electrical Assembly Authentication with Random Convolution Kernels and Fuzzy Extractors
inferred← citeshttps://doi.org/10.1007/978-3-032-06078-5_6openalex-snapshot
MASCOTS: Model-Agnostic Symbolic COunterfactual Explanations for Time Series
inferred← citeshttps://doi.org/10.1007/978-3-032-06106-5_14openalex-snapshot
Learning from Stochastic Teacher Representations Using Student-Guided Knowledge Distillation
inferred← citeshttps://doi.org/10.1007/978-3-032-06129-4_26openalex-snapshot
Time Series Machine Learning with Aeon: Classification and Regression
inferred← citeshttps://doi.org/10.1007/978-3-032-08330-2_14openalex-snapshot
Class-Dependent Perturbation Effects in Evaluating Time Series Attributions
inferred← citeshttps://doi.org/10.1007/978-3-032-11358-0_29openalex-snapshot
Convolutional Neural Network for Burst Detection in Water Pipes
inferred← citeshttps://doi.org/10.1007/978-3-032-15535-1_1openalex-snapshot
e-SMOTE: A Train Set Rebalancing Algorithm for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-15535-1_3openalex-snapshot
Re-framing Time Series Augmentation Through the Lens of Generative Models
inferred← citeshttps://doi.org/10.1007/978-3-032-15535-1_6openalex-snapshot
A Deep Dive into Alternatives to the Global Average Pooling for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-21582-6_22openalex-snapshot
Pyramid Features for Improved Functional Data Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-28079-4_14openalex-snapshot
Adversarial Robustness of Time-Series Classification for Crystal Collimator Alignment
inferred← citeshttps://doi.org/10.1007/978-3-032-31441-3_4openalex-snapshot
PACT: Motif Discovery in Time Series via Adaptive Segmentation, Symbolization, and Suffix Tree
inferred← citeshttps://doi.org/10.1007/978-3-032-31663-9_19openalex-snapshot
As-ECTS: Adaptive Shapelet Learning for Early Classification of Streaming Time Series
inferred← citeshttps://doi.org/10.1007/978-3-032-31933-3_35openalex-snapshot
TopGrad-CF: Gradient-Guided Counterfactual Explanations for Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-32729-1_48openalex-snapshot
Multimodal Physiological Ensemble Deep Learning for Driver’s Takeover Reaction Time Classification in Automated Vehicles
inferred← citeshttps://doi.org/10.1007/978-3-032-37670-1_30openalex-snapshot
K-VIC: Koopman Dynamics and Variance-Covariance Regularization for Time Series Representation
inferred← citeshttps://doi.org/10.1007/978-3-032-37676-3_13openalex-snapshot
A Warping Synthetic Minority Oversampling Technique for Imbalanced Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-3-032-37676-3_18openalex-snapshot
Efficient Sequence Processing With Linear Recurrent Reservoirs
inferred← citeshttps://doi.org/10.1007/978-3-032-37676-3_19openalex-snapshot
Generating Realistic Time-Series Counterfactuals via Diffusion-Guided Sampling
inferred← citeshttps://doi.org/10.1007/978-3-032-37676-3_26openalex-snapshot
Learning by Shifting: Temporal View Construction for Time Series Contrastive Learning
inferred← citeshttps://doi.org/10.1007/978-3-032-37676-3_32openalex-snapshot
TS2TabPFN: Time Series Classification and Extrinsic Regression Through Feature Extraction and a Tabular Foundation Model
inferred← citeshttps://doi.org/10.1007/978-3-032-39820-8_26openalex-snapshot
Deep Learning for Time Series Classification and Regression with aeon
inferred← citeshttps://doi.org/10.1007/978-981-16-2609-8_10openalex-snapshot
Time Series Classification Based on Complex Network
inferred← citeshttps://doi.org/10.1007/978-981-16-2712-5_57openalex-snapshot
A Brief Survey on Concept Drifted Data Stream Regression
inferred← citeshttps://doi.org/10.1007/978-981-19-6153-3_15openalex-snapshot
Deep Semi-supervised Learning for Time-Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-92-0071-9_14openalex-snapshot
Towards Plausibility in Time Series Counterfactual Explanations
inferred← citeshttps://doi.org/10.1007/978-981-92-2497-5_22openalex-snapshot
Semi-supervised Hierarchical Drift Detection via Prediction Uncertainty Distributions
inferred← citeshttps://doi.org/10.1007/978-981-92-2759-4_11openalex-snapshot
Cross-View Interaction and Collaboration for Semi-supervised Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-92-2888-1_34openalex-snapshot
Shape-Aware Compression of Streaming Data: An Online Dynamic Polynomial Selection Approach
inferred← citeshttps://doi.org/10.1007/978-981-92-3018-1_21openalex-snapshot
Verifiable Anomaly and Similarity Detection Using Matrix Profile in Private Time-series
inferred← citeshttps://doi.org/10.1007/978-981-95-2581-2_21openalex-snapshot
Can Time-Series Foundation Models Enhance Wireless Sensing Data Analytics? An Empirical Study
inferred← citeshttps://doi.org/10.1007/978-981-95-5699-1_1openalex-snapshot
Adaptive Downscaling on Inputs Improves Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-95-5761-5_14openalex-snapshot
DuetFormer: Learning a Time-Frequency Duet for Self-supervised Time Series Pre-training
inferred← citeshttps://doi.org/10.1007/978-981-96-0840-9_21openalex-snapshot
Improving Time Series Classification with Representation Soft Label Smoothing
inferred← citeshttps://doi.org/10.1007/978-981-96-0840-9_24openalex-snapshot
Kolmogorov-Arnold Networks (KAN) for Time Series Classification and Robust Analysis
inferred← citeshttps://doi.org/10.1007/978-981-96-2409-6_19openalex-snapshot
An Adversarial Attack Method for Multivariate Time Series Classification Based on AdvGAN
inferred← citeshttps://doi.org/10.1007/978-981-96-4016-4_9openalex-snapshot
Research on Time Series Classification Methods
inferred← citeshttps://doi.org/10.1007/978-981-96-8183-9_13openalex-snapshot
TrojanTime: Backdoor Attacks on Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-96-8197-6_20openalex-snapshot
Lightweight Defense Against Adversarial Attacks in Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-97-1711-8_5openalex-snapshot
Modeling Transitions of Inter-segment Patterns for Time Series Representation
inferred← citeshttps://doi.org/10.1007/978-981-97-2242-6_21openalex-snapshot
Local Subsequence-Based Distribution for Time Series Clustering
inferred← citeshttps://doi.org/10.1007/978-981-97-2266-2_22openalex-snapshot
Efficient and Accurate Similarity-Aware Graph Neural Network for Semi-supervised Time Series Classification
inferred← citeshttps://doi.org/10.1007/978-981-97-2650-9_10openalex-snapshot
Finding Foundation Models for Time Series Classification with a PreText Task
inferred← citeshttps://doi.org/10.1007/978-981-99-1639-9_4openalex-snapshot
The Context Hierarchical Contrastive Learning for Time Series in Frequency Domain
inferred← citeshttps://doi.org/10.1007/978-981-99-7872-4_21openalex-snapshot
Time Series Classification Based on Data-Augmented Contrastive Learning
inferred← citeshttps://doi.org/10.1007/978-981-99-9109-9_10openalex-snapshot
DDTM: A Distance-Based Data Transformation Method for Time Series Classification
inferred← citeshttps://doi.org/10.1007/s00170-024-13543-6openalex-snapshot
Steel surface roughness parameter prediction from laser reflection data using machine learning models
inferred← citeshttps://doi.org/10.1007/s00170-024-14225-zopenalex-snapshot
Predictive maintenance for wire drawing machine using MiniRocket and GA-based ensemble method
inferred← citeshttps://doi.org/10.1007/s00184-019-00746-1openalex-snapshot
Discriminant analysis based on binary time series
inferred← citeshttps://doi.org/10.1007/s00354-022-00165-3openalex-snapshot
Hyperparameter Optimization of Evolving Spiking Neural Network for Time-Series Classification
inferred← citeshttps://doi.org/10.1007/s00500-024-09928-0openalex-snapshot
Method of shapelet discovery for time series ordinal classification
inferred← citeshttps://doi.org/10.1007/s00500-025-10909-0openalex-snapshot
Dynamic shapelet selection with soft label for enhanced time series classification
inferred← citeshttps://doi.org/10.1007/s00521-022-07358-3openalex-snapshot
An active adaptation strategy for streaming time series classification based on elastic similarity measures
inferred← citeshttps://doi.org/10.1007/s00521-023-08459-3openalex-snapshot
Data Augmentation techniques in time series domain: a survey and taxonomy
inferred← citeshttps://doi.org/10.1007/s00521-023-09291-5openalex-snapshot
Speeding up pattern matching in streaming time-series via block vector and multilevel lower bound
inferred← citeshttps://doi.org/10.1007/s00521-024-10759-1openalex-snapshot
TransNAS-TSAD: harnessing transformers for multi-objective neural architecture search in time series anomaly detection
inferred← citeshttps://doi.org/10.1007/s00521-025-11550-6openalex-snapshot
Improving DNNs for time-series classification using state and gradient abstraction-based preprocessing
inferred← citeshttps://doi.org/10.1007/s00778-023-00832-xopenalex-snapshot
A new distributional treatment for time series anomaly detection
inferred← citeshttps://doi.org/10.1007/s10044-026-01742-8openalex-snapshot
Temporal Tree-Sliced Wasserstein distance for time-series data
inferred← citeshttps://doi.org/10.1007/s10115-021-01564-6openalex-snapshot
Efficient unsupervised drift detector for fast and high-dimensional data streams
inferred← citeshttps://doi.org/10.1007/s10115-022-01725-1openalex-snapshot
Elastic distances for time-series classification: Itakura versus Sakoe-Chiba constraints
inferred← citeshttps://doi.org/10.1007/s10115-022-01827-wopenalex-snapshot
Ultra-fast meta-parameter optimization for time series similarity measures with application to nearest neighbour classification
inferred← citeshttps://doi.org/10.1007/s10115-023-01855-0openalex-snapshot
Sequence likelihood divergence for fast time series comparison
inferred← citeshttps://doi.org/10.1007/s10115-023-01952-0openalex-snapshot
A review and evaluation of elastic distance functions for time series clustering
inferred← citeshttps://doi.org/10.1007/s10115-024-02107-5openalex-snapshot
C22MP: the marriage of catch22 and the matrix profile creates a fast, efficient and interpretable anomaly detector
inferred← citeshttps://doi.org/10.1007/s10115-026-02818-xopenalex-snapshot
Enhancing deep learning models for time series classification via knowledge distillation
inferred← citeshttps://doi.org/10.1007/s10462-022-10304-3openalex-snapshot
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
inferred← citeshttps://doi.org/10.1007/s10462-023-10468-6openalex-snapshot
Reinforcement learning for predictive maintenance: a systematic technical review
inferred← citeshttps://doi.org/10.1007/s10462-024-10995-wopenalex-snapshot
Revisiting streaming anomaly detection: benchmark and evaluation
inferred← citeshttps://doi.org/10.1007/s10489-019-01592-4openalex-snapshot
Evolutionary dataset optimisation: learning algorithm quality through evolution
inferred← citeshttps://doi.org/10.1007/s10489-021-02926-xopenalex-snapshot
Time Series Reconstruction and Classification: A Comprehensive Comparative Study
inferred← citeshttps://doi.org/10.1007/s10489-021-03009-7openalex-snapshot
Learning-based shapelets discovery by feature selection for time series classification
inferred← citeshttps://doi.org/10.1007/s10489-022-03485-5openalex-snapshot
Knowledge transfer via distillation from time and frequency domain for time series classification
inferred← citeshttps://doi.org/10.1007/s10489-022-03716-9openalex-snapshot
A method for measuring similarity of time series based on series decomposition and dynamic time warping
inferred← citeshttps://doi.org/10.1007/s10489-022-03755-2openalex-snapshot
Instance-based deep transfer learning with attention for stock movement prediction
inferred← citeshttps://doi.org/10.1007/s10489-022-03761-4openalex-snapshot
Target-class guided sample length reduction and training set selection of univariate time-series
inferred← citeshttps://doi.org/10.1007/s10489-022-03852-2openalex-snapshot
Accurate and fast time series classification based on compressed random Shapelet Forest
inferred← citeshttps://doi.org/10.1007/s10489-022-04043-9openalex-snapshot
A two-phase filtering of discriminative shapelets learning for time series classification
inferred← citeshttps://doi.org/10.1007/s10489-022-04386-3openalex-snapshot
FT-FVC: fast transformation-based feature vector concatenation for time series classification
inferred← citeshttps://doi.org/10.1007/s10489-022-04422-2openalex-snapshot
Localized shapelets selection for interpretable time series classification
inferred← citeshttps://doi.org/10.1007/s10489-023-04642-0openalex-snapshot
LSTMAE-DWSSLM: A unified approach for imbalanced time series data classification
inferred← citeshttps://doi.org/10.1007/s10489-023-04817-9openalex-snapshot
A framework for proposing a liquid stock portfolio using frequent itemset mining from time-series data
inferred← citeshttps://doi.org/10.1007/s10489-023-04859-zopenalex-snapshot
A time series classification method combining graph embedding and the bag-of-patterns algorithm
inferred← citeshttps://doi.org/10.1007/s10489-023-05029-xopenalex-snapshot
Variable-wise generative adversarial transformer in multivariate time series anomaly detection
inferred← citeshttps://doi.org/10.1007/s10489-023-05079-1openalex-snapshot
Multivariate time-series classification using memory and attention for long and short-term dependence$$^{\star }$$
inferred← citeshttps://doi.org/10.1007/s10489-024-05314-3openalex-snapshot
Missing data imputation and classification of small sample missing time series data based on gradient penalized adversarial multi-task learning
inferred← citeshttps://doi.org/10.1007/s10489-024-05672-yopenalex-snapshot
Discriminative shapelet learning via temporal clustering and matrix factorization
inferred← citeshttps://doi.org/10.1007/s10489-025-06444-yopenalex-snapshot
A comparison study of several strategies in multivariate time series clustering based on graph community detection
inferred← citeshttps://doi.org/10.1007/s10489-025-06551-wopenalex-snapshot
DifNet: Difference-based multi-resolution decomposition for time series anomaly detection
inferred← citeshttps://doi.org/10.1007/s10489-025-06752-3openalex-snapshot
Adaptive variable-length subsequence pattern extraction in time series
inferred← citeshttps://doi.org/10.1007/s10489-025-06798-3openalex-snapshot
Don’t get me wrong: How to apply deep visual interpretations to time series
inferred← citeshttps://doi.org/10.1007/s10489-025-06841-3openalex-snapshot
A graph convolutional network for time series classification using recurrence plots
inferred← citeshttps://doi.org/10.1007/s10586-024-04369-8openalex-snapshot
A-TSPD: autonomous-two stage algorithm for robust peak detection in online time series
inferred← citeshttps://doi.org/10.1007/s10618-019-00619-1openalex-snapshot
Deep learning for time series classification: a review
inferred← citeshttps://doi.org/10.1007/s10618-020-00679-8openalex-snapshot
TS-CHIEF: a scalable and accurate forest algorithm for time series classification
inferred← citeshttps://doi.org/10.1007/s10618-020-00695-8openalex-snapshot
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments
inferred← citeshttps://doi.org/10.1007/s10618-020-00701-zopenalex-snapshot
ROCKET: exceptionally fast and accurate time series classification using random convolutional kernels
inferred← citeshttps://doi.org/10.1007/s10618-020-00710-yopenalex-snapshot
InceptionTime: Finding AlexNet for time series classification
inferred← citeshttps://doi.org/10.1007/s10618-020-00727-3openalex-snapshot
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances
inferred← citeshttps://doi.org/10.1007/s10618-021-00740-0openalex-snapshot
Time series motifs discovery under DTW allows more robust discovery of conserved structure
inferred← citeshttps://doi.org/10.1007/s10618-021-00745-9openalex-snapshot
Time series extrinsic regression
inferred← citeshttps://doi.org/10.1007/s10618-021-00781-5openalex-snapshot
MultiETSC: automated machine learning for early time series classification
inferred← citeshttps://doi.org/10.1007/s10618-021-00782-4openalex-snapshot
Early abandoning and pruning for elastic distances including dynamic time warping
inferred← citeshttps://doi.org/10.1007/s10618-021-00796-yopenalex-snapshot
End-to-end deep representation learning for time series clustering: a comparative study
inferred← citeshttps://doi.org/10.1007/s10618-021-00798-wopenalex-snapshot
Time series clustering in linear time complexity
inferred← citeshttps://doi.org/10.1007/s10618-022-00828-1openalex-snapshot
Using p-values for the comparison of classifiers: pitfalls and alternatives
inferred← citeshttps://doi.org/10.1007/s10618-022-00844-1openalex-snapshot
MultiRocket: multiple pooling operators and transformations for fast and effective time series classification
inferred← citeshttps://doi.org/10.1007/s10618-022-00883-8openalex-snapshot
kNN matrix profile for knowledge discovery from time series
inferred← citeshttps://doi.org/10.1007/s10618-022-00898-1openalex-snapshot
Functional classwise principal component analysis: a classification framework for functional data analysis
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