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 2451–2500 of 6748 papers

TitleStatusHype
Decomposition-based hybrid wind speed forecasting model using deep bidirectional LSTM networks—0
Decomposing Temperature Time Series with Non-Negative Matrix Factorization—0
Attention-based Neural Load Forecasting: A Dynamic Feature Selection Approach—0
Decoding Working Memory Load from EEG with LSTM Networks—0
Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms—0
An autoencoder wavelet based deep neural network with attention mechanism for multistep prediction of plant growth—0
Decoding of visual-related information from the human EEG using an end-to-end deep learning approach—0
Decoding Multilingual Topic Dynamics and Trend Identification through ARIMA Time Series Analysis on Social Networks: A Novel Data Translation Framework Enhanced by LDA/HDP Models—0
Attention Augmented Convolutional Transformer for Tabular Time-series—0
Decoding Financial Health in Kenyas' Medical Insurance Sector: A Data-Driven Cluster Analysis—0
An Attention Free Long Short-Term Memory for Time Series Forecasting—0
Decoding dynamic brain patterns from evoked responses: A tutorial on multivariate pattern analysis applied to time-series neuroimaging data—0
Decoding Causality by Fictitious VAR Modeling—0
Decision-Aware Conditional GANs for Time Series Data—0
Deciphering Dynamical Nonlinearities in Short Time Series Using Recurrent Neural Networks—0
Attend and Diagnose: Clinical Time Series Analysis using Attention Models—0
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series—0
A Distributed Neural Network Architecture for Robust Non-Linear Spatio-Temporal Prediction—0
Decentralized Flood Forecasting Using Deep Neural Networks—0
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs—0
DDPG based on multi-scale strokes for financial time series trading strategy—0
A Tree-structure Convolutional Neural Network for Temporal Features Exaction on Sensor-based Multi-resident Activity Recognition—0
An Artificial Spiking Quantum Neuron—0
DBT-DMAE: An Effective Multivariate Time Series Pre-Train Model under Missing Data—0
Day Level Forecasting for Coronavirus Disease (COVID-19) Spread: Analysis, Modeling and Recommendations—0
Day-ahead time series forecasting: application to capacity planning—0
A transformer-based model for default prediction in mid-cap corporate markets—0
An Artificial Neural Network-based Stock Trading System Using Technical Analysis and Big Data Framework—0
Day-ahead electricity price prediction applying hybrid models of LSTM-based deep learning methods and feature selection algorithms under consideration of market coupling—0
DATSING: Data Augmented Time Series Forecasting with Adversarial Domain Adaptation—0
Data-Space Inversion Using a Recurrent Autoencoder for Time-Series Parameterization—0
Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison—0
A Transformer-based Deep Learning Algorithm to Auto-record Undocumented Clinical One-Lung Ventilation Events—0
An Applied Deep Learning Approach for Estimating Soybean Relative Maturity from UAV Imagery to Aid Plant Breeding Decisions—0
A Transfer-Learning Based Ensemble Architecture for ECG Signal Classification—0
Dataset Bias in Human Activity Recognition—0
A Trainable Reconciliation Method for Hierarchical Time-Series—0
An Anomaly Detection Method for Satellites Using Monte Carlo Dropout—0
A Direct Estimation of High Dimensional Stationary Vector Autoregressions—0
A Comparative Study of the Clinical use of Motion Analysis from Kinect Skeleton Data—0
A Bayesian Ensemble for Unsupervised Anomaly Detection—0
Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism—0
Data Quality Over Quantity: Pitfalls and Guidelines for Process Analytics—0
A topological analysis of cointegrated data: a Z24 Bridge case study—0
Data manipulation detection via permutation information theory quantifiers—0
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting—0
An analysis of deep neural networks for predicting trends in time series data—0
Data-Folding and Hyperspace Coding for Multi-Dimensonal Time-Series Data Imaging—0
Data Exploration and Validation on dense knowledge graphs for biomedical research—0
Data-Driven Time Series Reconstruction for Modern Power Systems Research—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