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 1176–1200 of 6748 papers

TitleStatusHype
Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open QuestionsCode0
Generative Adversarial Network for Future Hand Segmentation from Egocentric VideoCode0
Generalised Label-free Artefact Cleaning for Real-time Medical Pulsatile Time SeriesCode0
A Statistical Investigation of Long Memory in Language and MusicCode0
Mitigating Data Redundancy to Revitalize Transformer-based Long-Term Time Series Forecasting SystemCode0
General Domain Adaptation Through Proportional Progressive Pseudo LabelingCode0
AdaVol: An Adaptive Recursive Volatility Prediction MethodCode0
Gated Res2Net for Multivariate Time Series AnalysisCode0
GENDIS: GENetic DIscovery of ShapeletsCode0
Asset Price Forecasting using Recurrent Neural NetworksCode0
Fused-Lasso Regularized Cholesky Factors of Large Nonstationary Covariance Matrices of Longitudinal DataCode0
Fully Neural Network based Model for General Temporal Point ProcessesCode0
Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart HomesCode0
GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split AttentionCode0
General anesthesia reduces complexity and temporal asymmetry of the informational structures derived from neural recordings in DrosophilaCode0
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence FunctionsCode0
An accuracy-runtime trade-off comparison of scalable Gaussian process approximations for spatial dataCode0
Sequence Prediction using Spectral RNNsCode0
Assessing Differentially Private Variational Autoencoders under Membership InferenceCode0
Forecasting with Multiple SeasonalityCode0
A CNN adapted to time series for the classification of SupernovaeCode0
Forecasting the Leading Indicator of a Recession: The 10-Year minus 3-Month Treasury Yield SpreadCode0
Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of SnapchatCode0
Forecasting Time Series With Complex Seasonal Patterns Using Exponential SmoothingCode0
A Deep Dive into Perturbations as Evaluation Technique for Time Series XAICode0
Show:102550
← PrevPage 48 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