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 6501–6525 of 6748 papers

TitleStatusHype
Scalable Discovery of Time-Series Shapelets—0
Ranking and significance of variable-length similarity-based time series motifs—0
Telling cause from effect in deterministic linear dynamical systems—0
Low-dimensional Models in Spatio-Temporal Wind Speed Forecasting—0
Signal Processing on Graphs: Causal Modeling of Unstructured Data—0
Iteratively reweighted adaptive lasso for conditional heteroscedastic time series with applications to AR-ARCH type processes—0
Contour map of estimation error for Expected Shortfall—0
Temporal Embedding in Convolutional Neural Networks for Robust Learning of Abstract Snippets—0
Real time clustering of time series using triangular potentials—0
Generalized Gradient Learning on Time Series under Elastic Transformations—0
Exploring Transfer Function Nonlinearity in Echo State Networks—0
Variable and Fixed Interval Exponential Smoothing—0
Dependent Matérn Processes for Multivariate Time Series—0
Product Reservoir Computing: Time-Series Computation with Multiplicative Neurons—0
Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex SystemCode0
An Ordinal Pattern Approach to Detect and to Model Leverage Effects and Dependence Structures Between Financial Time Series—0
Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution—0
Particle swarm optimization for time series motif discovery—0
The search for candidate relevant subsets of variables in complex systems—0
The Western Africa Ebola virus disease epidemic exhibits both global exponential and local polynomial growth rates—0
A novel spectral method for inferring general diploid selection from time series genetic data—0
Data manipulation detection via permutation information theory quantifiers—0
Spatiotemporal clustering, climate periodicity, and social-ecological risk factors for dengue during an outbreak in Machala, Ecuador, in 2010—0
An Empirical Study of the L2-Boost technique with Echo State Networks—0
Efficiently Discovering Frequent Motifs in Large-scale Sensor Data—0
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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