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 4826–4850 of 6748 papers

TitleStatusHype
Local Score Dependent Model Explanation for Time Dependent Covariates—0
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal DimensionCode0
Wasserstein Index Generation Model: Automatic Generation of Time-series Index with Application to Economic Policy UncertaintyCode0
Learning towards Abstractive Timeline SummarizationCode0
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation—0
Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM—0
DeepAISE -- An End-to-End Development and Deployment of a Recurrent Neural Survival Model for Early Prediction of Sepsis—0
E2GAN: End-to-End Generative Adversarial Network or Multivariate Time Series Imputation—0
LSTM-based Flow Prediction—0
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classificationCode0
TEASER: Early and Accurate Time Series ClassificationCode0
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition—0
Modeling Extreme Events in Time Series Prediction—0
Identification of Effective Connectivity Subregions—0
NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data—0
Self-Organizing Maps with Variable Input Length for Motif Discovery and Word Segmentation—0
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network—0
Subspace Identification of Temperature DynamicsCode0
Model inference for Ordinary Differential Equations by parametric polynomial kernel regression—0
Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes—0
Chatter Detection in Turning Using Machine Learning and Similarity Measures of Time Series via Dynamic Time Warping—0
Adaptive-Halting Policy Network for Early ClassificationCode0
Developing an Unsupervised Real-time Anomaly Detection Scheme for Time Series with Multi-seasonality—0
Agglomerative Likelihood ClusteringCode0
Inferring linear and nonlinear Interaction networks using neighborhood support vector machines—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