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 2326–2350 of 6748 papers

TitleStatusHype
BLUnet: Arithmetic-free Inference with Bit-serialised Table Lookup Operation for Efficient Deep Neural Networks—0
Provably Calibrated Regression Under Distribution Drift—0
IIT-GAN: Irregular and Intermittent Time-series Synthesis with Generative Adversarial Networks—0
A Systematic Evaluation of Domain Adaptation Algorithms On Time Series Data—0
Context-invariant, multi-variate time series representations—0
Modeling Variable Space with Residual Tensor Networks for Multivariate Time Series—0
LatTe Flows: Latent Temporal Flows for Multivariate Sequence Analysis—0
TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting—0
Second-Order Neural ODE OptimizerCode1
Sequential Deep Learning Architectures for Anomaly Detection in Virtual Network Function Chains—0
Cross-Camera Human Motion Transfer by Time Series AnalysisCode0
Kernel distance measures for time series, random fields and other structured data—0
Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty—0
Adaptive Bayesian Sum of Trees Model for Covariate Dependent Spectral Analysis—0
Variational Inference for Continuous-Time Switching Dynamical Systems—0
Data-driven Residual Generation for Early Fault Detection with Limited Data—0
An Empirical Analysis of how Internet Access Influences Public Opinion towards Undocumented Immigrants and Unaccompanied ChildrenCode0
Macroeconomic forecasting with LSTM and mixed frequency time series data—0
Lithium-ion Battery State of Health Estimation based on Cycle Synchronization using Dynamic Time Warping—0
Random Dilated Shapelet Transform: A New Approach for Time Series ShapeletsCode1
The VVAD-LRS3 Dataset for Visual Voice Activity Detection—0
Improving Time Series Classification Algorithms Using Octave-Convolutional Layers—0
Anomaly Detection for High-Dimensional Data Using Large Deviations Principle—0
Neural ODE Processes: A Short SummaryCode1
Empirics on the expressiveness of Randomized Signature—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