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 3201–3225 of 6748 papers

TitleStatusHype
Improved Grey System Models for Predicting Traffic Parameters—0
Improved Modeling of Complex Systems Using Hybrid Physics/Machine Learning/Stochastic Models—0
Foreign Exchange Market Performance: Evidence from Bivariate Time Series Approach—0
Improved PAC-Bayesian Bounds for Linear Regression—0
Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model—0
Improved Predictive Deep Temporal Neural Networks with Trend Filtering—0
Complex-valued Gaussian Process Regression for Time Series Analysis—0
Improvement in Land Cover and Crop Classification based on Temporal Features Learning from Sentinel-2 Data Using Recurrent-Convolutional Neural Network (R-CNN)—0
Improvement of Flood Extent Representation with Remote Sensing Data and Data Assimilation—0
A review on distance based time series classification—0
A Method for Massively Parallel Analysis of Time Series—0
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis—0
Improving Astronomical Time-series Classification via Data Augmentation with Generative Adversarial Networks—0
A Data-Driven Approach for Modeling Stochasticity in Oil Market—0
Forecast with Forecasts: Diversity Matters—0
Improving Convolutional Neural Networks for Fault Diagnosis by Assimilating Global Features—0
ForecastTB An R Package as a Test-Bench for Time Series Forecasting Application of Wind Speed and Solar Radiation Modeling—0
Complex systems: features, similarity and connectivity—0
Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition—0
Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning—0
Improving Irregularly Sampled Time Series Learning with Dense Descriptors of Time—0
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data—0
Improving MF-DFA model with applications in precious metals market—0
Complex systems approach to natural language—0
A Review on Deep Learning in UAV Remote Sensing—0
Show:102550
← PrevPage 129 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