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Time Series Classification

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하위 태스크: 2
평가표: 52
보존된 평가 기록: 231

Time Series Classification is a general task that can be useful across many subject-matter domains and applications. The overall goal is to identify a time series as coming from one of possibly many sources or predefined groups, using labeled training data. That is, in this setting we conduct supervised learning, where the different time series sources are considered known.

Source: Nonlinear Time Series Classification Using Bispectrum-based Deep Convolutional Neural Networks

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://bitbucket.org/dataresearchlab/multiscale_dubuc

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Multiscale Dubuc: A New Similarity Measure for Time Series

https://bitbucket.org/lynn1/tcgan

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TCGAN: Convolutional Generative Adversarial Network for Time Series Classification and Clustering

https://github.com/ANR-MYEL/SelF-Rocket

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Time series classification with random convolution kernels based transforms: pooling operators and input representations matter

https://github.com/Atik-Ahamed/TSCMamba

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TSCMamba: Mamba Meets Multi-View Learning for Time Series Classification

https://github.com/BinhangYuan/WaveletFCNN

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WaveletAE: A Wavelet-enhanced Autoencoder for Wind Turbine Blade Icing Detection

https://github.com/BorealisAI/TSC-Disc-Proto

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Learning Discriminative Prototypes with Dynamic Time Warping

https://github.com/BorgwardtLab/Set_Functions_for_Time_Series

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Set Functions for Time Series

https://github.com/BorgwardtLab/mgp-tcn

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Early Recognition of Sepsis with Gaussian Process Temporal Convolutional Networks and Dynamic Time Warping

https://github.com/Castel44/SREA

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Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise

https://github.com/ChangWeiTan/MultiRocket

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MultiRocket: Multiple pooling operators and transformations for fast and effective time series classification

https://github.com/ChangWeiTan/TSRegression

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Monash University, UEA, UCR Time Series Extrinsic Regression Archive

https://github.com/DatrikIntelligence/SoundnessXAI

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On the Soundness of XAI in Prognostics and Health Management (PHM)

https://github.com/DominiqueMercier/PPML-TSA

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Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification

https://github.com/EvanZhuang/vector-icl

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Vector-ICL: In-context Learning with Continuous Vector Representations

https://github.com/FlaAI/TSFool-adversarial-time-series-generation-to-fool-RNNs

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TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective Attack

https://github.com/Frank-Wang-oss/TS-GAC

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Graph-Aware Contrasting for Multivariate Time-Series Classification

https://github.com/GTANAKA-LAB/Memristor-Network-Reservoir

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Simulation platform for pattern recognition based on reservoir computing with memristor networks

https://github.com/HerrmannM/paper-2021-EAPElasticDist

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Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping

https://github.com/IBCNServices/GENDIS

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GENDIS: GENetic DIscovery of Shapelets

https://github.com/Luckilyeee/M-CELS

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M-CELS: Counterfactual Explanation for Multivariate Time Series Data Guided by Learned Saliency Maps

https://github.com/ML-EDM/ML-EDM

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Open challenges for Machine Learning based Early Decision-Making research

https://github.com/MSD-IRIMAS/LITE

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Look Into the LITE in Deep Learning for Time Series Classification

https://github.com/Microsoft/EdgeML

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FastGRNN: A Fast, Accurate, Stable and Tiny Kilobyte Sized Gated Recurrent Neural Network

https://github.com/MonashTS/tempo

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Early Abandoning and Pruning for Elastic Distances including Dynamic Time Warping

https://github.com/NellyElsayed/GRU-FCN-model-for-univariate-time-series-classification

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Deep Gated Recurrent and Convolutional Network Hybrid Model for Univariate Time Series Classification

https://github.com/Oshana/ESWA

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A Comparison of Deep Learning and Established Methods for Calf Behaviour Monitoring

https://github.com/Surayez/EmotivDriverDistraction

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Classification of multivariate weakly-labelled time-series with attention

https://github.com/USC-InfoLab/NeuroGNN

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Dynamic GNNs for Precise Seizure Detection and Classification from EEG Data

https://github.com/VSainteuf/lightweight-temporal-attention-pytorch

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Lightweight Temporal Self-Attention for Classifying Satellite Image Time Series

https://github.com/VSainteuf/metric-guided-prototypes-pytorch

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Leveraging Class Hierarchies with Metric-Guided Prototype Learning

https://github.com/VSainteuf/pytorch-psetae

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Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention

https://github.com/VachelHU/ESGRN

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Time-Series Event Prediction with Evolutionary State Graph

https://github.com/VachelHU/EvoNet

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Time-Series Event Prediction with Evolutionary State Graph

https://github.com/WenjieDu/PyGrinder

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PyPOTS: A Python Toolbox for Data Mining on Partially-Observed Time Series

https://github.com/WenjieDu/PyPOTS

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Recurrent Neural Networks for Multivariate Time Series with Missing Values

https://github.com/WenjieDu/SAITS

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SAITS: Self-Attention-based Imputation for Time Series

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