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 4151–4200 of 6748 papers

TitleStatusHype
COVID-19 Public Opinion and Emotion Monitoring System Based on Time Series Thermal New Word Mining—0
Emotion-Inspired Deep Structure (EiDS) for EEG Time Series Forecasting—0
On the suitability of generalized regression neural networks for GNSS position time series prediction for geodetic applications in geodesy and geophysics—0
From learning gait signatures of many individuals to reconstructing gait dynamics of one single individual—0
Detecting and explaining changes in various assets' relationships in financial markets—0
RV-FuseNet: Range View Based Fusion of Time-Series LiDAR Data for Joint 3D Object Detection and Motion Forecasting—0
Neural Ordinary Differential Equation based Recurrent Neural Network Model—0
Neural ODEs for Informative Missingness in Multivariate Time Series—0
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models—0
Early Classification of Time Series. Cost-based Optimization Criterion and Algorithms—0
Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets—0
Necessary and sufficient conditions for causal feature selection in time series with latent common causes—0
Anomaly Detection in Cloud Components—0
Machine learning for the diagnosis of early stage diabetes using temporal glucose profiles—0
Epidemic parameters for COVID-19 in several regions of India—0
Tracking and tracing in the UK: a dynamic causal modelling study—0
Improving Neuroevolution Using Island Extinction and Repopulation—0
Temporal signals to images: Monitoring the condition of industrial assets with deep learning image processing algorithms—0
Echo State Networks trained by Tikhonov least squares are L2(μ) approximators of ergodic dynamical systems—0
Anomaly Detection And Classification In Time Series With Kervolutional Neural Networks—0
A network-based transfer learning approach to improve sales forecasting of new products—0
Multivariate non-Gaussian models for financial applications—0
Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic—0
A Novel Granular-Based Bi-Clustering Method of Deep Mining the Co-Expressed Genes—0
Observed and estimated prevalence of Covid-19 in Italy: Is it possible to estimate the total cases from medical swabs data?—0
Aortic Pressure Forecasting with Deep Sequence Learning—0
Propagation Graph Estimation from Individual's Time Series of Observed States—0
Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning—0
Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles—0
Interpretable Deep Representation Learning from Temporal Multi-view Data—0
Revealing hidden dynamics from time-series data by ODENet—0
A Multi-Variate Triple-Regression Forecasting Algorithm for Long-Term Customized Allergy Season Prediction—0
Probabilistic Multi-Step-Ahead Short-Term Water Demand Forecasting with Lasso—0
Temporal-Framing Adaptive Network for Heart Sound Segmentation without Prior Knowledge of State Duration—0
Social Media Information Sharing for Natural Disaster Response—0
Layer-wise training convolutional neural networks with smaller filters for human activity recognition using wearable sensors—0
Knowledge Enhanced Neural Fashion Trend ForecastingCode0
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University—0
On a computationally-scalable sparse formulation of the multidimensional and non-stationary maximum entropy principleCode0
Optimizing Temporal Convolutional Network inference on FPGA-based accelerators—0
Approaches and Applications of Early Classification of Time Series: A Review—0
Joint Multi-Dimensional Model for Global and Time-Series Annotations—0
P2ExNet: Patch-based Prototype Explanation Network—0
Deep convolutional generative adversarial networks for traffic data imputation encoding time series as images—0
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data—0
If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GANCode0
Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example—0
Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages—0
Cost-Effective Bad Synchrophasor Data Detection Based on Unsupervised Time Series Data Analytics—0
ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data—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