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

Showing 36013650 of 6748 papers

TitleStatusHype
Forecasting Short-term load using Econometrics time series model with T-student Distribution0
Anomaly Detection and Sampling Cost Control via Hierarchical GANs0
Inferring Global Dynamics Using a Learning Machine0
Instance-based Counterfactual Explanations for Time Series ClassificationCode1
Semi-Supervised Learning for In-Game Expert-Level Music-to-Dance Translation0
Piece-wise Matching Layer in Representation Learning for ECG Classification0
Decision-Aware Conditional GANs for Time Series Data0
A first econometric analysis of the CRIX family0
Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting0
Deep Learning based Covert Attack Identification for Industrial Control Systems0
Adversarial Examples in Deep Learning for Multivariate Time Series RegressionCode1
Cloud Cover Nowcasting with Deep Learning0
N-BEATS neural network for mid-term electricity load forecastingCode0
Limit Theorems for Factor Models0
A Linear Transportation L^p Distance for Pattern Recognition0
CoVaR with volatility clustering, heavy tails and non-linear dependence0
Vertical Power Flow Forecast with LSTMs Using Regular Training Update Strategies0
Breaking Symmetries of the Reservoir Equations in Echo State Networks0
A Time Series Data Analysis of Indian Commercial Dynamism0
Mapping horizontal and vertical urban densification in Denmark with Landsat time-series from 1985 to 2018: a semantic segmentation solution0
Survey of explainable machine learning with visual and granular methods beyond quasi-explanations0
Resilient In-Season Crop Type Classification in Multispectral Satellite Observations using Growth Stage NormalizationCode0
Latent State Inference in a Spatiotemporal Generative Model0
From Static to Dynamic Node Embeddings0
A Sequential Modelling Approach for Indoor Temperature Prediction and Heating Control in Smart Buildings0
Subjective Metrics-based Cloud Market Performance Prediction0
Transient Classification in low SNR Gravitational Wave data using Deep Learning0
Stock Price Prediction Using Machine Learning and LSTM-Based Deep Learning ModelsCode1
"Hey, that's not an ODE": Faster ODE Adjoints via SeminormsCode3
Gated Res2Net for Multivariate Time Series AnalysisCode0
Evaluation of Local Explanation Methods for Multivariate Time Series Forecasting0
Explainable boosted linear regression for time series forecasting0
TODS: An Automated Time Series Outlier Detection SystemCode2
Identification of Abnormal States in Videos of Ants Undergoing Social Phase ChangeCode0
Recurrent Graph Tensor Networks: A Low-Complexity Framework for Modelling High-Dimensional Multi-Way Sequence0
Forecasting time series with encoder-decoder neural networks0
Time-series Imputation and Prediction with Bi-Directional Generative Adversarial NetworksCode1
Neural Rough Differential Equations for Long Time SeriesCode1
Automatic deep learning for trend prediction in time series data0
Indoor environment data time-series reconstruction using autoencoder neural networks0
Time series forecasting with Gaussian Processes needs priorsCode1
Tropical time series, iterated-sums signatures and quasisymmetric functionsCode0
Simplicial persistence of financial markets: filtering, generative processes and portfolio risk0
Time your hedge with Deep Reinforcement Learning0
Matrix Profile XXII: Exact Discovery of Time Series Motifs under DTWCode0
An analysis of deep neural networks for predicting trends in time series data0
Efficient Variational Bayes Learning of Graphical Models with Smooth Structural Changes0
TadGAN: Time Series Anomaly Detection Using Generative Adversarial NetworksCode2
Online nonnegative CP-dictionary learning for Markovian dataCode0
Show:102550
← PrevPage 73 of 135Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified