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 276–300 of 6748 papers

TitleStatusHype
Large Models for Time Series and Spatio-Temporal Data: A Survey and OutlookCode4
OBSUM: An object-based spatial unmixing model for spatiotemporal fusion of remote sensing imagesCode1
A Survey of Feature Types and Their Contributions for Camera Tampering Detection—0
Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs—0
TimeGPT-1Code4
Comparing Time-Series Analysis Approaches Utilized in Research Papers to Forecast COVID-19 Cases in Africa: A Literature Review—0
NoxTrader: LSTM-Based Stock Return Momentum Prediction for Quantitative Trading—0
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter AveragingCode0
Diffeomorphic Transformations for Time Series Analysis: An Efficient Approach to Nonlinear Warping—0
Predicting Temperature of Major Cities Using Machine Learning and Deep Learning—0
From Text to Trends: A Unique Garden Analytics Perspective on the Future of Modern Agriculture—0
Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential ReconstructionCode1
ISLAND: Interpolating Land Surface Temperature using land coverCode0
A detection analysis for temporal memory patterns at different time-scales—0
Human Activity Segmentation Challenge @ ECML/PKDD’23Code1
Learning Beyond Similarities: Incorporating Dissimilarities between Positive Pairs in Self-Supervised Time Series Learning—0
Market-GAN: Adding Control to Financial Market Data Generation with Semantic ContextCode1
Agriculture Credit and Economic Growth in Bangladesh: A Time Series Analysis—0
PhysioZoo: The Open Digital Physiological Biomarkers Resource—0
Time Series Analysis of Urban Liveability—0
Predicting Financial Market Trends using Time Series Analysis and Natural Language Processing—0
Evaluating Explanation Methods for Multivariate Time Series ClassificationCode0
Hierarchical Time Series Forecasting with Bayesian Modeling—0
High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods—0
Path Signatures for Seizure Forecasting—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