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 76–100 of 6748 papers

TitleStatusHype
CORAL: Concept Drift Representation Learning for Co-evolving Time-series—0
Bridging Simplicity and Sophistication using GLinear: A Novel Architecture for Enhanced Time Series PredictionCode0
Multivariate Human Activity Segmentation: Systematic Benchmark with ClaSPCode0
Text Classification: Neural Networks VS Machine Learning Models VS Pre-trained Models—0
Econometric Analysis of Pandemic Disruption and Recovery Trajectory in the U.S. Rail Freight Industry—0
AverageTime: Enhance Long-Term Time Series Forecasting with Simple AveragingCode0
A Survey on Time-Series Distance Measures—0
Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems—0
Hidformer: Transformer-Style Neural Network in Stock Price Forecasting—0
Revisiting PCA for time series reduction in temporal dimensionCode7
Adopting Trustworthy AI for Sleep Disorder Prediction: Deep Time Series Analysis with Temporal Attention Mechanism and Counterfactual Explanations—0
CNN-LSTM Hybrid Deep Learning Model for Remaining Useful Life Estimation—0
Using matrix-product states for time-series machine learningCode1
TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series AnalysisCode1
GG-SSMs: Graph-Generating State Space Models—0
Are Large Language Models Useful for Time Series Data Analysis?—0
ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual DataCode2
Federated Foundation Models on Heterogeneous Time SeriesCode1
GAF-FusionNet: Multimodal ECG Analysis via Gramian Angular Fields and Split AttentionCode0
UTSD: Unified Time Series Diffusion Model—0
ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and ReasoningCode3
MuSiCNet: A Gradual Coarse-to-Fine Framework for Irregularly Sampled Multivariate Time Series Analysis—0
DSSRNN: Decomposition-Enhanced State-Space Recurrent Neural Network for Time-Series AnalysisCode0
A Wave is Worth 100 Words: Investigating Cross-Domain Transferability in Time Series—0
A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant informationCode0
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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