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 4751–4800 of 6748 papers

TitleStatusHype
Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team ScenarioCode0
Independence Testing for Temporal Data—0
eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart ChairCode0
Comprehensive Time-Series Regression Models Using GRETL -- U.S. GDP and Government Consumption Expenditures & Gross Investment from 1980 to 2013—0
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks—0
Locally Linear Embedding and fMRI feature selection in psychiatric classification—0
HOTVis: Higher-Order Time-Aware Visualisation of Dynamic Graphs—0
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded EmbeddingCode0
A Machine Learning Approach for Smartphone-based Sensing of Roads and Driving Style—0
Mixed pooling of seasonality for time series forecasting: An application to pallet transport data—0
Towards automated symptoms assessment in mental health—0
MEx: Multi-modal Exercises Dataset for Human Activity RecognitionCode0
Local Score Dependent Model Explanation for Time Dependent Covariates—0
Wasserstein Index Generation Model: Automatic Generation of Time-series Index with Application to Economic Policy UncertaintyCode0
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal DimensionCode0
Learning towards Abstractive Timeline SummarizationCode0
E2GAN: End-to-End Generative Adversarial Network or Multivariate Time Series Imputation—0
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation—0
DeepAISE -- An End-to-End Development and Deployment of a Recurrent Neural Survival Model for Early Prediction of Sepsis—0
Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM—0
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classificationCode0
LSTM-based Flow Prediction—0
TEASER: Early and Accurate Time Series ClassificationCode0
Modeling Extreme Events in Time Series Prediction—0
Identification of Effective Connectivity Subregions—0
Sparse Coding of Shape Trajectories for Facial Expression and Action Recognition—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
Subspace Identification of Temperature DynamicsCode0
Modelling Segmented Cardiotocography Time-Series Signals Using One-Dimensional Convolutional Neural Networks for the Early Detection of Abnormal Birth Outcomes—0
Model inference for Ordinary Differential Equations by parametric polynomial kernel regression—0
Classification of Hand Movements from EEG using a Deep Attention-based LSTM Network—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
Linear Dynamics: Clustering without identificationCode0
Inferring linear and nonlinear Interaction networks using neighborhood support vector machines—0
Agglomerative Likelihood ClusteringCode0
Unsupervised Representation Learning and Anomaly Detection in ECG Sequences—0
An L0-Norm Constrained Non-Negative Matrix Factorization Algorithm for the Simultaneous Disaggregation of Fixed and Shiftable Loads—0
Anti-Money Laundering in Bitcoin: Experimenting with Graph Convolutional Networks for Financial ForensicsCode0
Large-scale directed network inference with multivariate transfer entropy and hierarchical statistical testing—0
An anomaly prediction framework for financial IT systems using hybrid machine learning methods—0
Time Series Analysis of Big Data for Electricity Price and Demand to Find Cyber-Attacks part 2: Decomposition Analysis—0
Is type 1 diabetes a chaotic phenomenon?—0
Multi-modal Predictive Models of Diabetes Progression—0
Context Model for Pedestrian Intention Prediction using Factored Latent-Dynamic Conditional Random FieldsCode0
Classification of chaotic time series with deep learning—0
Deep Learning Detection of Inaccurate Smart Electricity Meters: A Case StudyCode0
Scalable Dictionary Classifiers for Time Series ClassificationCode0
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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