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 2276–2300 of 6748 papers

TitleStatusHype
Automatic Generation of Student Report Cards—0
Automatic Generation of Probabilistic Programming from Time Series Data—0
Deep Learning with Long Short-Term Memory for Time Series Prediction—0
Deep Learning with Kernel Flow Regularization for Time Series Forecasting—0
Automatic Forecasting via Meta-Learning—0
A Neural Network-Based On-device Learning Anomaly Detector for Edge Devices—0
Adversarial Domain Adaptation for Stable Brain-Machine Interfaces—0
A Composite Quantile Fourier Neural Network for Multi-Step Probabilistic Forecasting of Nonstationary Univariate Time Series—0
A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves—0
Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgery—0
Deep Learning with Attention Mechanism for Predicting Driver Intention at Intersection—0
On model selection for scalable time series forecasting in transport networks—0
Deep Learning to Attend to Risk in ICU—0
Automatic estimation of heading date of paddy rice using deep learning—0
A Neural Implementation of the Kalman Filter—0
Deep Learning, Predictability, and Optimal Portfolio Returns—0
Deep learning of contagion dynamics on complex networks—0
Automatic Error Analysis of Human Motor Performance for Interactive Coaching in Virtual Reality—0
An Euler-based GAN for time series—0
Deep-Learning Inversion of Seismic Data—0
Automatic Detection Of Noise Events at Shooting Range Using Machine Learning—0
Deep Learning in Multiple Multistep Time Series Prediction—0
Deep Learning in Asset Pricing—0
Automatic Detection of Major Freeway Congestion Events Using Wireless Traffic Sensor Data: A Machine Learning Approach—0
Automatic Detection of Interplanetary Coronal Mass Ejections in Solar Wind In Situ Data—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