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

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Showing 2751–2775 of 6748 papers

TitleStatusHype
Enhancing keyword correlation for event detection in social networks using SVD and k-means: Twitter case study—0
Forecasting Player Behavioral Data and Simulating in-Game Events—0
A Systematic Comparison of Forecasting for Gross Domestic Product in an Emergent Economy—0
Forecasting Realized Volatility Matrix With Copula-Based Models—0
Causal Inference via Kernel Deviance Measures—0
A Novel Markov Model for Near-Term Railway Delay Prediction—0
Forecasting Short-term load using Econometrics time series model with T-student Distribution—0
Forecasting Soil Moisture Using Domain Inspired Temporal Graph Convolution Neural Networks To Guide Sustainable Crop Management—0
Local-Global Methods for Generalised Solar Irradiance Forecasting—0
Forecasting Solar Power Generation on the basis of Predictive and Corrective Maintenance Activities—0
Forecasting Spatio-Temporal Renewable Scenarios: a Deep Generative Approach—0
Forecasting the abnormal events at well drilling with machine learning—0
Forecasting The JSE Top 40 Using Long Short-Term Memory Networks—0
A review of predictive uncertainty estimation with machine learning—0
Generalised learning of time-series: Ornstein-Uhlenbeck processes—0
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning—0
Causal Inference from Slowly Varying Nonstationary Processes—0
Compensatory model for quantile estimation and application to VaR—0
Forecasting time series with encoder-decoder neural networks—0
Forecasting Time Series with VARMA Recursions on Graphs—0
Forecasting trends with asset prices—0
Forecasting under Long Memory and Nonstationarity—0
Forecasting Using Reservoir Computing: The Role of Generalized Synchronization—0
Forecasting with a Panel Tobit Model—0
Enhancing Energy System Models Using Better Load Forecasts—0
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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