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 5776–5800 of 6748 papers

TitleStatusHype
Temporal Stability in Predictive Process MonitoringCode0
Long-Range Correlation Underlying Childhood Language and Generative Models—0
RNN-based counterfactual prediction, with an application to homestead policy and public schoolingCode0
Comparative analysis of criteria for filtering time series of word usage frequencies—0
Learning User Intent from Action Sequences on Interactive Systems—0
Temporal Attention augmented Bilinear Network for Financial Time-Series Data AnalysisCode0
TrueSkill Through Time: Revisiting the History of ChessCode0
YASS: Yet Another Spike SorterCode0
Random Projection Filter Bank for Time Series Data—0
Dynamic-Depth Context Tree Weighting—0
Practical Data-Dependent Metric Compression with Provable Guarantees—0
Subset Selection and Summarization in Sequential Data—0
Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories—0
Discriminative State Space Models—0
Preventing Gradient Explosions in Gated Recurrent Units—0
Multivariate Time Series Classification with WEASEL+MUSECode0
A Neural Stochastic Volatility Model—0
A Multi-Horizon Quantile Recurrent ForecasterCode0
Role of Deep LSTM Neural Networks And WiFi Networks in Support of Occupancy Prediction in Smart Buildings—0
OSTSC: Over Sampling for Time Series Classification in R—0
Forecasting of a Hierarchical Functional Time Series on Example of Macromodel for Day and Night Air Pollution in Silesia Region: A Critical Overview—0
Warped-Linear Models for Time Series Classification—0
Random matrix approach to estimation of high-dimensional factor models—0
Variational Encoding of Complex DynamicsCode0
An Efficient ADMM Algorithm for Structural Break Detection in Multivariate Time Series—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