SOTAVerified

Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

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Showing 151–175 of 6748 papers

TitleStatusHype
Large Pre-trained time series models for cross-domain Time series analysis tasksCode1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
A Multi-Scale Decomposition MLP-Mixer for Time Series AnalysisCode1
OBSUM: An object-based spatial unmixing model for spatiotemporal fusion of remote sensing imagesCode1
Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential ReconstructionCode1
Human Activity Segmentation Challenge @ ECML/PKDD’23Code1
Market-GAN: Adding Control to Financial Market Data Generation with Semantic ContextCode1
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization ApproachCode1
Network Traffic Classification based on Single Flow Time Series AnalysisCode1
BeliefPPG: Uncertainty-aware Heart Rate Estimation from PPG signals via Belief PropagationCode1
Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal BootstrappingCode1
Improving Position Encoding of Transformers for Multivariate Time Series ClassificationCode1
SMPConv: Self-moving Point Representations for Continuous ConvolutionCode1
OneShotSTL: One-Shot Seasonal-Trend Decomposition For Online Time Series Anomaly Detection And ForecastingCode1
Time Series Segmentation Applied to a New Data Set for Mobile Sensing of Human ActivitiesCode1
UniTS: A Universal Time Series Analysis Framework Powered by Self-Supervised Representation LearningCode1
Spacecraft Anomaly Detection with Attention Temporal Convolution NetworkCode1
TSMixer: An All-MLP Architecture for Time Series ForecastingCode1
Vector Quantized Time Series Generation with a Bidirectional Prior ModelCode1
Synthetic ECG Signal Generation using Probabilistic Diffusion ModelsCode1
TimeMAE: Self-Supervised Representations of Time Series with Decoupled Masked AutoencodersCode1
Stock Broad-Index Trend Patterns Learning via Domain Knowledge Informed Generative NetworkCode1
A Synthetic Texas Power System with Time-Series Weather-Dependent Spatiotemporal ProfilesCode1
LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation -- Extended VersionCode1
LightCTS: A Lightweight Framework for Correlated Time Series ForecastingCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47—Unverified
2GRU-D - APC (n = 1)F127.3—Unverified
3GRU-APC (n = 1)F125.7—Unverified
4GRU-DF122.5—Unverified
5GRUF122.3—Unverified
6GRU-SimpleF122.2—Unverified
7GRU-MeanF122.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51—Unverified
2ViT% Test Accuracy98.11—Unverified
3FlexTCN-4% Test Accuracy97.73—Unverified
4MatchboxNet% Test Accuracy97.4—Unverified
5CKCNN (100k)% Test Accuracy95.27—Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73—Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13—Unverified