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 1101–1125 of 6748 papers

TitleStatusHype
Financial Time-Series Forecasting: Towards Synergizing Performance And Interpretability Within a Hybrid Machine Learning Approach—0
POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning—0
The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models—0
CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting—0
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis—0
Using deep neural networks to improve the precision of fast-sampled particle timing detectors—0
Signatures Meet Dynamic Programming: Generalizing Bellman Equations for Trajectory Following—0
Personalized Pose Forecasting—0
MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts—0
An Adaptive Framework for Generalizing Network Traffic Prediction towards Uncertain Environments—0
A projected nonlinear state-space model for forecasting time series signalsCode0
Linear-time online visibility graph transformation algorithm: for both natural and horizontal visibility criteria—0
Estimating optical vegetation indices and biophysical variables for temperate forests with Sentinel-1 SAR data using machine learning techniques: A case study for CzechiaCode0
Time Scale Network: A Shallow Neural Network For Time Series Data—0
On the Opportunities of Green Computing: A Survey—0
A Systematic Review for Transformer-based Long-term Series Forecasting—0
Raising the ClaSS of Streaming Time Series SegmentationCode0
Triple Simplex Matrix Completion for Expense Forecasting—0
Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach—0
Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs—0
A Survey of Feature Types and Their Contributions for Camera Tampering Detection—0
Comparing Time-Series Analysis Approaches Utilized in Research Papers to Forecast COVID-19 Cases in Africa: A Literature Review—0
NoxTrader: LSTM-Based Stock Return Momentum Prediction for Quantitative Trading—0
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter AveragingCode0
Diffeomorphic Transformations for Time Series Analysis: An Efficient Approach to Nonlinear Warping—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