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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–125 of 6748 papers

TitleStatusHype
A Survey of Time Series Foundation Models: Generalizing Time Series Representation with Large Language ModelCode2
Position: What Can Large Language Models Tell Us about Time Series AnalysisCode2
FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series ForecastingCode2
Harnessing Vision Models for Time Series Analysis: A SurveyCode2
Deep learning for time series classification: a reviewCode2
Deep learning for time series classificationCode2
Satellite Image Time Series Analysis for Big Earth Observation DataCode2
SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image UnderstandingCode2
Self-supervised Contrastive Representation Learning for Semi-supervised Time-Series ClassificationCode2
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series ForecastingCode2
Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic ForecastingCode2
DeepAR: Probabilistic Forecasting with Autoregressive Recurrent NetworksCode2
Learning Deep Time-index Models for Time Series ForecastingCode2
TadGAN: Time Series Anomaly Detection Using Generative Adversarial NetworksCode2
Closed-form Continuous-time Neural ModelsCode2
ADATIME: A Benchmarking Suite for Domain Adaptation on Time Series DataCode2
Conformal prediction interval for dynamic time-seriesCode2
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual DataCode2
TODS: An Automated Time Series Outlier Detection SystemCode2
CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series ForecastingCode2
Diffusion-based Time Series Imputation and Forecasting with Structured State Space ModelsCode2
A Survey on Deep Learning based Time Series Analysis with Frequency TransformationCode2
Classification of Raw MEG/EEG Data with Detach-Rocket Ensemble: An Improved ROCKET Algorithm for Multivariate Time Series AnalysisCode1
CAMul: Calibrated and Accurate Multi-view Time-Series ForecastingCode1
A biologically plausible neural network for Slow Feature AnalysisCode1
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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