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 1501–1525 of 6748 papers

TitleStatusHype
Convolutional Mixture Density Recurrent Neural Network for Predicting User Location with WiFi Fingerprints—0
Convolutional Neural Network-Bagged Decision Tree: A hybrid approach to reduce electric vehicle's driver's range anxiety by estimating energy consumption in real-time—0
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation—0
Convolutional Neural Networks: Basic Concepts and Applications in Manufacturing—0
Convolutional Neural Networks for Time-dependent Classification of Variable-length Time Series—0
A Robust Score-Driven Filter for Multivariate Time Series—0
Asset correlation estimation for inhomogeneous exposure pools—0
Convolutional Sequence Modeling Revisited—0
Conditional independence testing with a single realization of a multivariate nonstationary nonlinear time series—0
Convolutional-Sparse-Coded Dynamic Mode Decomposition and Its Application to River State Estimation—0
A Modified Dynamic Time Warping (MDTW) Approach and Innovative Average Non-Self Match Distance (ANSD) Method for Anomaly Detection in ECG Recordings—0
Day-ahead time series forecasting: application to capacity planning—0
ConvTimeNet: A Deep Hierarchical Fully Convolutional Model for Multivariate Time Series Analysis—0
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification—0
Coordinating users of shared facilities via data-driven predictive assistants and game theory—0
Asset volatility forecasting:The optimal decay parameter in the EWMA model—0
DBT-DMAE: An Effective Multivariate Time Series Pre-Train Model under Missing Data—0
Copy the dynamics using a learning machine—0
Conditional heteroskedasticity in crypto-asset returns—0
Core-Collapse Supernova Gravitational-Wave Search and Deep Learning Classification—0
Core Network Management Procedures for Self-Organized and Sustainable 5G Cellular Networks—0
Coresets for Kernel Regression—0
Coresets for k-Segmentation of Streaming Data—0
Coresets for Time Series Clustering—0
Conditional Generative Models for Counterfactual Explanations—0
Show:102550
← PrevPage 61 of 270Next →
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