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 1226–1250 of 6748 papers

TitleStatusHype
ATM Cash demand forecasting in an Indian Bank with chaos and deep learning—0
Analyzing Time Series Changes of Correlation between Market Share and Concerns on Companies measured through Search Engine Suggests—0
A Time-Series Scale Mixture Model of EEG with a Hidden Markov Structure for Epileptic Seizure Detection—0
A Time Series Multitask Framework Integrating a Large Language Model, Pre-Trained Time Series Model, and Knowledge Graph—0
A comparative study of statistical and machine learning models on near-real-time daily emissions prediction—0
Comprehensive Time-Series Regression Models Using GRETL -- U.S. GDP and Government Consumption Expenditures & Gross Investment from 1980 to 2013—0
A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors—0
A detection analysis for temporal memory patterns at different time-scales—0
A Time-Series Distribution Test System Based on Real Utility Data—0
A time series distance measure for efficient clustering of input output signals by their underlying dynamics—0
Analyzing high-dimensional time-series data using kernel transfer operator eigenfunctions—0
A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport—0
A Time Series Data Analysis of Indian Commercial Dynamism—0
A Time Series Approach To Player Churn and Conversion in Videogames—0
A dependent partition-valued process for multitask clustering and time evolving network modelling—0
Interpretable Classification of Early Stage Parkinson's Disease from EEG—0
A Time Series Approach to Explainability for Neural Nets with Applications to Risk-Management and Fraud Detection—0
Analytics of Business Time Series Using Machine Learning and Bayesian Inference—0
A Comparative Study of Reservoir Computing for Temporal Signal Processing—0
Composition Properties of Inferential Privacy for Time-Series Data—0
Compressive Nonparametric Graphical Model Selection For Time Series—0
A Time Series Analysis of Emotional Loading in Central Bank Statements—0
A Time Series Analysis-Based Stock Price Prediction Using Machine Learning and Deep Learning Models—0
Analysis, Online Estimation, and Validation of a Competing Virus Model—0
A Time Series Analysis-Based Forecasting Framework for the Indian Healthcare Sector—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