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 1876–1900 of 6748 papers

TitleStatusHype
COVID-19 forecasting using new viral variants and vaccination effectiveness models—0
Balanced Graph Structure Learning for Multivariate Time Series ForecastingCode0
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative ModelsCode0
SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud RemovalCode1
Neural Architecture Searching for Facial Attributes-based Depression Recognition—0
Forgery Attack Detection in Surveillance Video Streams Using Wi-Fi Channel State Information—0
Simulating Using Deep Learning The World Trade Forecasting of Export-Import Exchange Rate Convergence Factor During COVID-19—0
Fast Transient Stability Prediction Using Grid-informed Temporal and Topological Embedding Deep Neural Network—0
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series—0
Imposing Connectome-Derived Topology on an Echo State Network—0
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting—0
MIDAS: Deep learning human action intention prediction from natural eye movement patterns—0
Spatiotemporal Analysis Using Riemannian Composition of Diffusion Operators—0
Dynamic Deep Convolutional Candlestick Learner—0
Has EU accession boosted patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models—0
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented PopulationsCode0
Long Short-Term Memory Neural Network for Financial Time Series—0
Lead-lag detection and network clustering for multivariate time series with an application to the US equity market—0
A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the Covid-19 caseCode0
TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series DataCode2
Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1D Convolutional Neural Network Approach—0
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data—0
Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health RecordsCode0
Online Time Series Anomaly Detection with State Space Gaussian Processes—0
GTrans: Spatiotemporal Autoregressive Transformer with Graph Embeddings for Nowcasting Extreme Events—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