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 4151–4175 of 6748 papers

TitleStatusHype
COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining—0
Emotion-Inspired Deep Structure (EiDS) for EEG Time Series Forecasting—0
On the suitability of generalized regression neural networks for GNSS position time series prediction for geodetic applications in geodesy and geophysics—0
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual—0
Detecting and explaining changes in various assets' relationships in financial markets—0
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting—0
Neural Ordinary Differential Equation based Recurrent Neural Network Model—0
Neural ODEs for Informative Missingness in Multivariate Time Series—0
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models—0
Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms—0
Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets—0
Necessary and sufficient conditions for causal feature selection in time series with latent common causes—0
Anomaly Detection in Cloud Components—0
Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles—0
Epidemic parameters for COVID-19 in several regions of India—0
Tracking and tracing in the UK: a dynamic causal modelling study—0
Improving Neuroevolution Using Island Extinction and Repopulation—0
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
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
A network-based transfer learning approach to improve sales forecasting of new products—0
Multivariate non-Gaussian models for financial applications—0
Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic—0
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes—0
Observed and estimated prevalence of Covid-19 in Italy: Is it possible to estimate the total cases from medical swabs data?—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