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 4026–4050 of 6748 papers

TitleStatusHype
Anomaly Detection in Cloud Components—0
Necessary and sufficient conditions for causal feature selection in time series with latent common causes—0
Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles—0
Neural Controlled Differential Equations for Irregular Time SeriesCode1
Tracking and tracing in the UK: a dynamic causal modelling study—0
Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 StudyCode1
DEFM: Delay E mbedding based Forecast Machine for Time Series Forecasting by Spatiotemporal Information TransformationCode1
Improving Neuroevolution Using Island Extinction and Repopulation—0
RED: Deep Recurrent Neural Networks for Sleep EEG Event DetectionCode1
AtsPy: Automated Time Series Forecasting in PythonCode1
Temporal signals to images: Monitoring the condition of industrial assets with deep learning image processing algorithms—0
Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems—0
Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image RepresentationCode1
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
Multivariate non-Gaussian models for financial applications—0
A network-based transfer learning approach to improve sales forecasting of new products—0
Observed and estimated prevalence of Covid-19 in Italy: Is it possible to estimate the total cases from medical swabs data?—0
Aortic Pressure Forecasting with Deep Sequence Learning—0
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes—0
Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic—0
Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles—0
Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning—0
Interpretable Deep Representation Learning from Temporal Multi-view Data—0
Revealing hidden dynamics from time-series data by ODENet—0
Propagation Graph Estimation from Individual's Time Series of Observed States—0
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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