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 1526–1550 of 6748 papers

TitleStatusHype
Coronavirus (COVID-19): ARIMA based time-series analysis to forecast near future—0
A statistical test of market efficiency based on information theory—0
Correcting motion induced fluorescence artifacts in two-channel neural imaging—0
Conditional Mutual information-based Contrastive Loss for Financial Time Series Forecasting—0
Correlated Time Series Forecasting using Deep Neural Networks: A Summary of Results—0
Kernel Hypothesis Testing with Set-valued Data—0
A Robust Score-Driven Filter for Multivariate Time Series—0
Correlations and Flow of Information between The New York Times and Stock Markets—0
Correlation-wise Smoothing: Lightweight Knowledge Extraction for HPC Monitoring Data—0
Conditional independence testing with a single realization of a multivariate nonstationary nonlinear time series—0
Cost-Effective Bad Synchrophasor Data Detection Based on Unsupervised Time Series Data Analytics—0
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings—0
A Stochastic Time Series Model for Predicting Financial Trends using NLP—0
A Strategy Optimized Pix2pix Approach for SAR-to-Optical Image Translation Task—0
Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification—0
Decomposition of Time Series Data of Stock Markets and its Implications for Prediction: An Application for the Indian Auto Sector—0
Deconvolution of the Functional Ultrasound Response in the Mouse Visual Pathway Using Block-Term Decomposition—0
Conditional heteroskedasticity in crypto-asset returns—0
CoughTrigger: Earbuds IMU Based Cough Detection Activator Using An Energy-efficient Sensitivity-prioritized Time Series Classifier—0
Conditional Generative Models for Counterfactual Explanations—0
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow—0
COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction—0
Coupled Recurrent Models for Polyphonic Music Composition—0
Conditional Generative Adversarial Networks to Model Urban Outdoor Air Pollution—0
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics—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