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 2451–2475 of 6748 papers

TitleStatusHype
Fast-Slow Streamflow Model Using Mass-Conserving LSTM—0
Evaluation of Local Explanation Methods for Multivariate Time Series Forecasting—0
Evaluation of Spectral Learning for the Identification of Hidden Markov Models—0
Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models—0
Ensemble neuroevolution based approach for multivariate time series anomaly detection—0
Evaluation of Time Series Forecasting Models for Estimation of PM2.5 Levels in Air—0
Towards Automatic Forecasting: Evaluation of Time-Series Forecasting Models for Chickenpox Cases Estimation in Hungary—0
Chatter Detection in Turning Using Machine Learning and Similarity Measures of Time Series via Dynamic Time Warping—0
Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction—0
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection—0
Causal Structural Learning from Time Series: A Convex Optimization Approach—0
Evidence of disorientation towards immunization on online social media after contrasting political communication on vaccines. Results from an analysis of Twitter data in Italy—0
Ensemble Grammar Induction For Detecting Anomalies in Time Series—0
A Novel Multi-Centroid Template Matching Algorithm and Its Application to Cough Detection—0
Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities—0
Evolutionary Ensemble Learning for Multivariate Time Series Prediction—0
A Pipeline for Graph-Based Monitoring of the Changes in the Information Space of Russian Social Media during the Lockdown—0
Integrating Fréchet distance and AI reveals the evolutionary trajectory and origin of SARS-CoV-2—0
Adaptive Complementary Ensemble EMD and Energy-Frequency Spectra of Cryptocurrency Prices—0
Evolution of Hierarchical Structure & Reuse in iGEM Synthetic DNA Sequences—0
Evolving Gaussian Process kernels from elementary mathematical expressions—0
Choosing Wavelet Methods, Filters, and Lengths for Functional Brain Network Construction—0
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting—0
Exact and Robust Conformal Inference Methods for Predictive Machine Learning With Dependent Data—0
Ensemble Forecasting of Monthly Electricity Demand using Pattern Similarity-based Methods—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