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 1576–1600 of 6748 papers

TitleStatusHype
Deep-ESN: A Multiple Projection-encoding Hierarchical Reservoir Computing Framework—0
Crop Type Identification for Smallholding Farms: Analyzing Spatial, Temporal and Spectral Resolutions in Satellite Imagery—0
Crop Yield Prediction Integrating Genotype and Weather Variables Using Deep Learning—0
Cross-border Commodity Pricing Strategy Optimization via Mixed Neural Network for Time Series Analysis—0
Cross-Dimensional Self-Attention for Multivariate, Geo-tagged Time Series Imputation—0
DeepFIB: Self-Imputation for Time Series Anomaly Detection—0
Cross-Frequency Time Series Meta-Forecasting—0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
Crossmatching variable objects with the Gaia data—0
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition—0
Cross-Modal Data Programming Enables Rapid Medical Machine Learning—0
Analysis of cyclical behavior in time series of stock market returns—0
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data—0
Cross-Modal Virtual Sensing for Combustion Instability Monitoring—0
Asymptotic nonparametric statistical analysis of stationary time series—0
Deep Learning based Covert Attack Identification for Industrial Control Systems—0
Cross-Recurrence Quantification Analysis of Categorical and Continuous Time Series: an R package—0
Cross-Subject Domain Adaptation for Classifying Working Memory Load with Multi-Frame EEG Images—0
Crowdfunding Dynamics Tracking: A Reinforcement Learning Approach—0
Deep Learning for Satellite Image Time Series Analysis: A Review—0
Cryptocurrency Market Consolidation in 2020--2021—0
Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk—0
Concentration inequalities for correlated network-valued processes with applications to community estimation and changepoint analysis—0
cs-net: structural approach to time-series forecasting for high-dimensional feature space data with limited observations—0
Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets—0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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