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 201–225 of 6748 papers

TitleStatusHype
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential EquationsCode1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
Changing Fashion CulturesCode1
Random Dilated Shapelet Transform: A New Approach for Time Series ShapeletsCode1
ADformer: A Multi-Granularity Transformer for EEG-Based Alzheimer's Disease AssessmentCode1
Copula Conformal Prediction for Multi-step Time Series ForecastingCode1
A Generalised Signature Method for Multivariate Time Series Feature ExtractionCode1
Contrastive Domain Adaptation for Time-Series via Temporal MixupCode1
COVID-19 Data Analysis and Forecasting: Algeria and the WorldCode1
Adjusting for Autocorrelated Errors in Neural Networks for Time SeriesCode1
A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecastingCode1
Crop mapping from image time series: deep learning with multi-scale label hierarchiesCode1
Domain Adaptation for Time Series Forecasting via Attention SharingCode1
Self-Supervised Time Series Representation Learning via Cross Reconstruction TransformerCode1
Data Generating Process to Evaluate Causal Discovery Techniques for Time Series DataCode1
Data Normalization for Bilinear Structures in High-Frequency Financial Time-seriesCode1
Change Point Detection in Time Series Data using Autoencoders with a Time-Invariant RepresentationCode1
Advancing the State-of-the-Art for ECG Analysis through Structured State Space ModelsCode1
Chaos as an interpretable benchmark for forecasting and data-driven modellingCode1
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural NetworksCode1
Decoupling Local and Global Representations of Time SeriesCode1
Deep Adaptive Input Normalization for Time Series ForecastingCode1
Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural NetworksCode1
catch22: CAnonical Time-series CHaracteristicsCode1
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
Show:102550
← PrevPage 9 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