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 1351–1400 of 6748 papers

TitleStatusHype
A State-Space Approach to Dynamic Nonnegative Matrix Factorization—0
A CNN–LSTM model for gold price time-series forecasting—0
Creating Disasters: Recession Forecasting with GAN-Generated Synthetic Time Series Data—0
A State Space Approach for Piecewise-Linear Recurrent Neural Networks for Reconstructing Nonlinear Dynamics from Neural Measurements—0
Asset volatility forecasting:The optimal decay parameter in the EWMA model—0
An Adaptive Framework for Generalizing Network Traffic Prediction towards Uncertain Environments—0
Asset Pricing with General Transaction Costs: Theory and Numerics—0
Asset Pricing and Deep Learning—0
A CNN based method for Sub-pixel Urban Land Cover Classification using Landsat-5 TM and Resourcesat-1 LISS-IV Imagery—0
An Adaptive Approach for Anomaly Detector Selection and Fine-Tuning in Time Series—0
Asset correlation estimation for inhomogeneous exposure pools—0
A Deep Learning Approach for Motion Forecasting Using 4D OCT Data—0
Assessment of electrical and infrastructure recovery in Puerto Rico following hurricane Maria using a multisource time series of satellite imagery—0
Assessing the Potential of AI for Spatially Sensitive Nature-Related Financial Risks—0
An Active Learning Framework with a Class Balancing Strategy for Time Series Classification—0
A Bayesian Approach for Predicting Food and Beverage Sales in Staff Canteens and Restaurants—0
Creating cloud-free satellite imagery from image time series with deep learning—0
Assessing the Impact of Distribution Shift on Reinforcement Learning Performance—0
Assessing the effect of advertising expenditures upon sales: a Bayesian structural time series model—0
An Accurate Smartphone Battery Parameter Calibration Using Unscented Kalman Filter—0
Assessing Social License to Operate from the Public Discourse on Social Media—0
Assessing Lower Limb Strength using Internet-of-Things Enabled Chair—0
A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles—0
A Bayesian analysis of gain-loss asymmetry—0
Assessing biological models using topological data analysis—0
A Deep Learning Approach for Forecasting Air Pollution in South Korea Using LSTM—0
A Spectral Enabled GAN for Time Series Data Generation—0
A Spectral Algorithm for Learning Hidden Markov Models—0
A Multi-View Framework for BGP Anomaly Detection via Graph Attention Network—0
COVID-19: Tail Risk and Predictive Regressions—0
COVID-19: The extraction of the effective reproduction number from the time series of new cases—0
A specifically designed machine learning algorithm for GNSS position time series prediction and its applications in outlier and anomaly detection and earthquake prediction—0
A Multi-Variate Triple-Regression Forecasting Algorithm for Long-Term Customized Allergy Season Prediction—0
A Spatial-Temporal Graph Based Hybrid Infectious Disease Model with Application to COVID-19—0
A Multi-Scale Tensor Network Architecture for Classification and Regression—0
A Deep Learning Approach for COVID-19 Trend Prediction—0
A Spatial-Temporal Decomposition Based Deep Neural Network for Time Series Forecasting—0
A Soft Computing Approach for Selecting and Combining Spectral Bands—0
A multi-scale symmetry analysis of uninterrupted trends returns of daily financial indices—0
A Single Scalable LSTM Model for Short-Term Forecasting of Disaggregated Electricity Loads—0
A Clustering Algorithm for Correlation Quickest Hub Discovery Mixing Time Evolution and Random Matrix Theory—0
Differential Recurrent Neural Network and its Application for Human Activity Recognition—0
COVID-19 forecasting using new viral variants and vaccination effectiveness models—0
CRATOS: Cognition of Reliable Algorithm for Time-series Optimal Solution—0
A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting—0
A simulation of the insurance industry: The problem of risk model homogeneity—0
A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter—0
A Multi-Phase Approach for Product Hierarchy Forecasting in Supply Chain Management: Application to MonarchFx Inc—0
A similarity measurement for time series and its application to the stock market—0
A Multi-modal Deep Learning Model for Video Thumbnail Selection—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