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 1926–1950 of 6748 papers

TitleStatusHype
DANNTe: a case study of a turbo-machinery sensor virtualization under domain shift—0
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019—0
Application of Common Spatial Patterns in Gravitational Waves Detection—0
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?—0
Data-driven approach in a compartmental epidemic model to assess undocumented infectionsCode0
A machine learning search for optimal GARCH parameters—0
OPP-Miner: Order-preserving sequential pattern mining—0
Weak Supervision for Affordable Modeling of Electrocardiogram Data—0
Causal Discovery from Sparse Time-Series Data Using Echo State Network—0
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Forecasting with Application to Electricity DemandCode0
Unifying Epidemic Models with Mixtures—0
Bayesian Online Change Point Detection for Baseline Shifts—0
An Improved Mathematical Model of Sepsis: Modeling, Bifurcation Analysis, and Optimal Control Study for Complex Nonlinear Infectious Disease System—0
Detecting CAN Masquerade Attacks with Signal Clustering Similarity—0
Applications of Signature Methods to Market Anomaly Detection—0
Churn prediction in online gambling—0
Approximate Factor Models for Functional Time SeriesCode0
Time Series Forecasting Using Fuzzy Cognitive Maps: A Survey—0
Second-Order Ultrasound Elastography with L1-norm Spatial Regularization—0
Bitcoin Price Predictive Modeling Using Expert Correction—0
Bayesian Regression Approach for Building and Stacking Predictive Models in Time Series Analytics—0
Introducing Randomized High Order Fuzzy Cognitive Maps as Reservoir Computing Models: A Case Study in Solar Energy and Load Forecasting—0
Sales Time Series Analytics Using Deep Q-Learning—0
Classification of Long Sequential Data using Circular Dilated Convolutional Neural NetworksCode1
Towards Similarity-Aware Time-Series ClassificationCode1
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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