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 1251–1275 of 6748 papers

TitleStatusHype
Analysis of Wide and Deep Echo State Networks for Multiscale Spatiotemporal Time Series Forecasting—0
A Deep Structural Model for Analyzing Correlated Multivariate Time Series—0
A textual transform of multivariate time-series for prognostics—0
A Comparative Study of Detecting Anomalies in Time Series Data Using LSTM and TCN Models—0
A Tempt to Unify Heterogeneous Driving Databases using Traffic Primitives—0
A Temporal Fusion Transformer for Long-term Explainable Prediction of Emergency Department Overcrowding—0
Analysis of stock index with a generalized BN-S model: an approach based on machine learning and fuzzy parameters—0
A Bayesian Deep Learning Framework for End-To-End Prediction of Emotion from Heartbeat—0
Cellular Traffic Prediction and Classification: a comparative evaluation of LSTM and ARIMA—0
Analysis of Nonstationary Time Series Using Locally Coupled Gaussian Processes—0
A tale of two toolkits, report the second: bake off redux. Chapter 1. dictionary based classifiers—0
A Comparative Study: Adaptive Fuzzy Inference Systems for Energy Prediction in Urban Buildings—0
A tale of two toolkits, report the first: benchmarking time series classification algorithms for correctness and efficiency—0
Empirical Analysis of Lifelog Data using Optimal Feature Selection based Unsupervised Logistic Regression (OFS-ULR) Model with Spark Streaming—0
A deep network approach to multitemporal cloud detection—0
Confidence Interval Construction for Multivariate time series using Long Short Term Memory Network—0
A Tale of Tail Covariances (and Diversified Tails)—0
A tail dependence-based MST and their topological indicators in modelling systemic risk in the European insurance sector—0
Analysis of Hydrological and Suspended Sediment Events from Mad River Watershed using Multivariate Time Series Clustering—0
A Systematic Review for Transformer-based Long-term Series Forecasting—0
A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification—0
Analysis of Empirical Mode Decomposition-based Load and Renewable Time Series Forecasting—0
A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services—0
Confident Kernel Sparse Coding and Dictionary Learning—0
Configuration and Collection Factors for Side-Channel Disassembly—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