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

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Showing 251–275 of 6748 papers

TitleStatusHype
The Rise of Diffusion Models in Time-Series ForecastingCode3
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
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis—0
CSformer: Combining Channel Independence and Mixing for Robust Multivariate Time Series Forecasting—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
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series ClassificationCode1
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
Understanding the Role of Textual Prompts in LLM for Time Series Forecasting: an Adapter ViewCode1
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
Large Pre-trained time series models for cross-domain Time series analysis tasksCode1
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
Raising the ClaSS of Streaming Time Series SegmentationCode0
A Systematic Review for Transformer-based Long-term Series Forecasting—0
Triple Simplex Matrix Completion for Expense Forecasting—0
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
A Multi-Scale Decomposition MLP-Mixer for Time Series AnalysisCode1
Unveiling Early Warning Signals of Systemic Risks in Banks: A Recurrence Network-Based Approach—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