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 3076–3100 of 6748 papers

TitleStatusHype
An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves—0
High Dimensional Time Series Generators—0
High-dimensional Time Series Prediction with Missing Values—0
High Dimensional Time Series Regression Models: Applications to Statistical Learning Methods—0
Higher-order Cross-structural Embedding Model for Time Series Analysis—0
HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs—0
High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach—0
A Novel Framework for Handling Sparse Data in Traffic Forecast—0
Improved Prediction and Network Estimation Using the Monotone Single Index Multi-variate Autoregressive Model—0
Improved Predictive Deep Temporal Neural Networks with Trend Filtering—0
End-to-End Fine-Grained Action Segmentation and Recognition Using Conditional Random Field Models and Discriminative Sparse Coding—0
A GRU-based Mixture Density Network for Data-Driven Dynamic Stochastic Programming—0
Automatic Model Building in GEFCom 2017 Qualifying Match—0
Optimizing Bayesian Recurrent Neural Networks on an FPGA-based Accelerator—0
High-recall causal discovery for autocorrelated time series with latent confounders—0
Emulating dynamic non-linear simulators using Gaussian processes—0
High-Resolution Satellite Imagery for Modeling the Impact of Aridification on Crop Production—0
A Novel Ensemble Deep Learning Model for Stock Prediction Based on Stock Prices and News—0
HiPPO-KAN: Efficient KAN Model for Time Series Analysis—0
Improved PAC-Bayesian Bounds for Linear Regression—0
Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics—0
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting—0
Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting—0
Empowering Time Series Analysis with Large Language Models: A Survey—0
Empowering Time Series Analysis with Synthetic Data: A Survey and Outlook in the Era of Foundation Models—0
Show:102550
← PrevPage 124 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