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 126–150 of 6748 papers

TitleStatusHype
Positional Encoding in Transformer-Based Time Series Models: A SurveyCode1
Time Series Embedding Methods for Classification Tasks: A ReviewCode1
Using matrix-product states for time-series machine learningCode1
TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled Multivariate Time Series AnalysisCode1
Federated Foundation Models on Heterogeneous Time SeriesCode1
Peri-midFormer: Periodic Pyramid Transformer for Time Series AnalysisCode1
Abstracted Shapes as Tokens -- A Generalizable and Interpretable Model for Time-series ClassificationCode1
Reconstructing dynamics from sparse observations with no training on target systemCode1
Towards Generalisable Time Series Understanding Across DomainsCode1
Toward Physics-guided Time Series EmbeddingCode1
Neural Fourier Modelling: A Highly Compact Approach to Time-Series AnalysisCode1
Can LLMs Understand Time Series Anomalies?Code1
Time Series Analysis for Education: Methods, Applications, and Future DirectionsCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
Classification of Raw MEG/EEG Data with Detach-Rocket Ensemble: An Improved ROCKET Algorithm for Multivariate Time Series AnalysisCode1
SigKAN: Signature-Weighted Kolmogorov-Arnold Networks for Time SeriesCode1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesCode1
Time Series Representation ModelsCode1
Heracles: A Hybrid SSM-Transformer Model for High-Resolution Image and Time-Series AnalysisCode1
Self-Supervised Learning for Time Series: Contrastive or Generative?Code1
MTSA-SNN: A Multi-modal Time Series Analysis Model Based on Spiking Neural NetworkCode1
PatchAD: A Lightweight Patch-based MLP-Mixer for Time Series Anomaly DetectionCode1
DualDynamics: Synergizing Implicit and Explicit Methods for Robust Irregular Time Series AnalysisCode1
Series2Vec: Similarity-based Self-supervised Representation Learning for Time Series ClassificationCode1
Understanding the Role of Textual Prompts in LLM for Time Series Forecasting: an Adapter ViewCode1
Show:102550
← PrevPage 6 of 270Next →
All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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