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 2826–2850 of 6748 papers

TitleStatusHype
Enhanced Cyber-Physical Security through Deep Learning Techniques—0
Conditional Generative Models for Counterfactual Explanations—0
Fully convolutional networks for structural health monitoring through multivariate time series classification—0
Fully Learnable Deep Wavelet Transform for Unsupervised Monitoring of High-Frequency Time Series—0
Conditional heteroskedasticity in crypto-asset returns—0
Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality—0
A Novel Hybrid Framework for Hourly PM2.5 Concentration Forecasting Using CEEMDAN and Deep Temporal Convolutional Neural Network—0
Functional Bayesian Filter—0
Functional Classwise Principal Component Analysis: A Novel Classification Framework—0
Functional Connectivity Dynamics show Resting-State Instability and Rightward Parietal Dysfunction in ADHD—0
Functional Mixtures-of-Experts—0
Functional Time Series Forecasting: Functional Singular Spectrum Analysis Approaches—0
Detection and Forecasting of Extreme event in Stock Price Triggered by Fundamental, Technical, and External Factors—0
Bayesian Neural Networks for Macroeconomic Analysis—0
Fused Lasso for Feature Selection using Structural Information—0
Fusing Continuous-valued Medical Labels using a Bayesian Model—0
Fusing Deep Learned and Hand-Crafted Features of Appearance, Shape, and Dynamics for Automatic Pain Estimation—0
Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processes—0
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning—0
Fuzzy Cognitive Maps and Hidden Markov Models: Comparative Analysis of Efficiency within the Confines of the Time Series Classification Task—0
Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms—0
Fuzzy Longest Common Subsequence Matching With FCM Using R—0
FV-MgNet: Fully Connected V-cycle MgNet for Interpretable Time Series Forecasting—0
Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows—0
Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals—0
Show:102550
← PrevPage 114 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