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 676–700 of 6748 papers

TitleStatusHype
FedTADBench: Federated Time-Series Anomaly Detection BenchmarkCode1
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for HealthcareCode1
Financial Time Series Data Processing for Machine LearningCode1
Feature-Based Time-Series Analysis in R using the theft PackageCode1
CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact DataCode1
Crop mapping from image time series: deep learning with multi-scale label hierarchiesCode1
A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series DataCode1
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series ImputationCode1
A Review of Graph Neural Networks and Their Applications in Power SystemsCode1
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time WarpingCode1
Self-Supervised Time Series Representation Learning via Cross Reconstruction TransformerCode1
An Accurate and Fully-Automated Ensemble Model for Weekly Time Series ForecastingCode1
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution TestsCode1
Monash Time Series Forecasting ArchiveCode1
Monash University, UEA, UCR Time Series Extrinsic Regression ArchiveCode1
Motiflets -- Simple and Accurate Detection of Motifs in Time SeriesCode1
Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging DataCode1
MrSQM: Fast Time Series Classification with Symbolic RepresentationsCode1
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed LaplacianCode1
Data Normalization for Bilinear Structures in High-Frequency Financial Time-seriesCode1
ASTRIDE: Adaptive Symbolization for Time Series DatabasesCode1
Are we certain it's anomalous?Code1
Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin PlateCode1
ARMA Cell: A Modular and Effective Approach for Neural Autoregressive ModelingCode1
An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series ClassificationCode1
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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