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 5176–5200 of 6748 papers

TitleStatusHype
Online Estimation of Multiple Dynamic Graphs in Pattern Sequences—0
Online Evolutionary Neural Architecture Search for Multivariate Non-Stationary Time Series Forecasting—0
Online false discovery rate control for anomaly detection in time series—0
Online Forecasting Matrix Factorization—0
Online Graph Topology Learning from Matrix-valued Time Series—0
Online Hierarchical Forecasting for Power Consumption Data—0
Online Joint Topology Identification and Signal Estimation from Streams with Missing Data—0
Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes—0
Online learning of both state and dynamics using ensemble Kalman filters—0
Online Learning of the Kalman Filter with Logarithmic Regret—0
Online learning of windmill time series using Long Short-term Cognitive Networks—0
Online Learning with Predictable Sequences—0
Online Learning with Radial Basis Function Networks—0
Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks—0
Online Non-linear Topology Identification from Graph-connected Time Series—0
Online Real-time Learning of Dynamical Systems from Noisy Streaming Data: A Koopman Operator Approach—0
OnlineSTL: Scaling Time Series Decomposition by 100x—0
On-line Summarization of Time-series Documents using a Graph-based Algorithm—0
Online Supervised Subspace Tracking—0
Online Time Series Anomaly Detection with State Space Gaussian Processes—0
Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalisation—0
On Lyapunov exponents and adversarial perturbation—0
On Merging Feature Engineering and Deep Learning for Diagnosis, Risk-Prediction and Age Estimation Based on the 12-Lead ECG—0
On Multivariate Financial Time Series Classification—0
On Multivariate Singular Spectrum Analysis and its Variants—0
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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