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 5901–5950 of 6748 papers

TitleStatusHype
Cost-Sensitive Convolution based Neural Networks for Imbalanced Time-Series Classification—0
Cough Detection Using Hidden Markov Models—0
CoughTrigger: Earbuds IMU Based Cough Detection Activator Using An Energy-efficient Sensitivity-prioritized Time Series Classifier—0
Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy—0
COUnty aggRegation mixup AuGmEntation (COURAGE) COVID-19 Prediction—0
Coupled Recurrent Models for Polyphonic Music Composition—0
Covariance-engaged Classification of Sets via Linear Programming—0
Covariance shrinkage for autocorrelated data—0
CoVaR with volatility clustering, heavy tails and non-linear dependence—0
Modeling Macroeconomic Variations After COVID-19—0
COVID-19 Hospitalizations Forecasts Using Internet Search Data—0
Covid-19 impact on cryptocurrencies: evidence from a wavelet-based Hurst exponent—0
COVID-19 infection and recovery in various countries: Modeling the dynamics and evaluating the non-pharmaceutical mitigation scenarios—0
COVID-19 Outbreak Prediction and Analysis using Self Reported Symptoms—0
COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining—0
COVID-19 forecasting using new viral variants and vaccination effectiveness models—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
CRATOS: Cognition of Reliable Algorithm for Time-series Optimal Solution—0
Creating cloud-free satellite imagery from image time series with deep learning—0
Creating Disasters: Recession Forecasting with GAN-Generated Synthetic Time Series Data—0
A Critical Overview of Privacy-Preserving Approaches for Collaborative Forecasting—0
Critical Transitions in Intensive Care Units: A Sepsis Case Study—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
Cross-Frequency Time Series Meta-Forecasting—0
Cross-Lingual Topic Alignment in Time Series Japanese / Chinese News—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
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data—0
Cross-Modal Virtual Sensing for Combustion Instability Monitoring—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
Correlation recurrent units: A novel neural architecture for improving the predictive performance of time-series data—0
Cryptocurrency Market Consolidation in 2020--2021—0
Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk—0
cs-net: structural approach to time-series forecasting for high-dimensional feature space data with limited observations—0
Cumulative Stay-time Representation for Electronic Health Records in Medical Event Time Prediction—0
Currency exchange prediction using machine learning, genetic algorithms and technical analysis—0
Current state of nonlinear-type time-frequency analysis and applications to high-frequency biomedical signals—0
Curriculum Learning in Deep Neural Networks for Financial Forecasting—0
Cyclical Electromechanical Error Denial System Using Matrix Profile—0
Cyclocopula Technique to Study the Relationship Between Two Cyclostationary Time Series with Fractional Brownian Motion Errors—0
D2KE: From Distance to Kernel and Embedding—0
DAE : Discriminatory Auto-Encoder for multivariate time-series anomaly detection in air transportation—0
Daily Middle-Term Probabilistic Forecasting of Power Consumption in North-East England—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