https://github.com/timeseriesAI/tsai
Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline
Papers with Code 아카이브
Time Series Classification
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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://github.com/timeseriesAI/tsai/blob/main/tsai/models/InceptionTime.py
InceptionTime: Finding AlexNet for Time Series Classification
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/MINIROCKET_Pytorch.py
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/RNN_FCN.py
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/TST.py
A Transformer-based Framework for Multivariate Time Series Representation Learning
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/XCM.py
XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/XceptionTime.py
https://github.com/timeseriesAI/tsai/blob/main/tsai/models/mWDN.py
Multilevel Wavelet Decomposition Network for Interpretable Time Series Analysis
https://github.com/timeseriesAI/tsai/tree/main/tsai/models
LSTM Fully Convolutional Networks for Time Series Classification
https://github.com/titu1994/Adversarial-Attacks-Time-Series
https://github.com/titu1994/LSTM-FCN-Ablation
Insights into LSTM Fully Convolutional Networks for Time Series Classification
https://github.com/titu1994/MLSTM-FCN
LSTM Fully Convolutional Networks for Time Series Classification
https://github.com/uea-machine-learning/tsml
Scalable Dictionary Classifiers for Time Series Classification
https://github.com/vc1492a/tidd
Imaging Time-Series to Improve Classification and Imputation
https://github.com/weitianxin/awesome-distribution-shift
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift
https://github.com/westny/neural-stability
https://github.com/xingyu617/SimTS_Representation_Learning
https://github.com/yuhao-3/ACTLL
The UEA multivariate time series classification archive, 2018
https://github.com/zdcuob/Fully-Convlutional-Neural-Networks-for-state-of-the-art-time-series-classification-
Multi-Scale Convolutional Neural Networks for Time Series Classification
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.