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 251300 of 6748 papers

TitleStatusHype
Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecastingCode1
Sinusoidal Frequency Estimation by Gradient DescentCode1
TILDE-Q: A Transformation Invariant Loss Function for Time-Series ForecastingCode1
FingerFlex: Inferring Finger Trajectories from ECoG signalsCode1
SpectraNet: Multivariate Forecasting and Imputation under Distribution Shifts and Missing DataCode1
Neural ODEs as Feedback Policies for Nonlinear Optimal ControlCode1
Anytime-valid off-policy inference for contextual banditsCode1
Soil moisture estimation from Sentinel-1 interferometric observations over arid regionsCode1
TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency AnalysisCode1
Improving Medical Predictions by Irregular Multimodal Electronic Health Records ModelingCode1
Dynamic Topological Data Analysis of Functional Human Brain NetworksCode1
Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep LearningCode1
A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFIDCode1
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series ForecastingCode1
Deep Counterfactual Estimation with Categorical Background VariablesCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
Transformer-based conditional generative adversarial network for multivariate time series generationCode1
Learning Signal Temporal Logic through Neural Network for Interpretable ClassificationCode1
Unsupervised Model Selection for Time-series Anomaly DetectionCode1
Finding Scientific Topics in Continuously Growing Text CorporaCode1
Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised LearningCode1
Neural parameter calibration for large-scale multi-agent modelsCode1
A Deep Learning Approach to Analyzing Continuous-Time SystemsCode1
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye SemanticsCode1
DeepVARwT: Deep Learning for a VAR Model with TrendCode1
PromptCast: A New Prompt-based Learning Paradigm for Time Series ForecastingCode1
Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin PlateCode1
Understanding of the properties of neural network approaches for transient light curve approximationsCode1
Scalable Spatiotemporal Graph Neural NetworksCode1
TSFool: Crafting Highly-Imperceptible Adversarial Time Series through Multi-Objective AttackCode1
Autoencoder Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering AlgorithmCode1
W-Transformers : A Wavelet-based Transformer Framework for Univariate Time Series ForecastingCode1
Time-distance vision transformers in lung cancer diagnosis from longitudinal computed tomographyCode1
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed LaplacianCode1
Light curve completion and forecasting using fast and scalable Gaussian processes (MuyGPs)Code1
ARMA Cell: A Modular and Effective Approach for Neural Autoregressive ModelingCode1
SoMoFormer: Multi-Person Pose Forecasting with TransformersCode1
Spatio-Temporal Wind Speed Forecasting using Graph Networks and Novel Transformer ArchitecturesCode1
Global RTK Positioning in Graphical State SpaceCode1
AA-Forecast: Anomaly-Aware Forecast for Extreme EventsCode1
Stop&Hop: Early Classification of Irregular Time SeriesCode1
From Time Series to Networks in R with the ts2net PackageCode1
Simulation-Informed Revenue Extrapolation with Confidence Estimate for Scaleup Companies Using Scarce Time-Series DataCode1
An Unsupervised Short- and Long-Term Mask Representation for Multivariate Time Series Anomaly DetectionCode1
Expressing Multivariate Time Series as Graphs with Time Series Attention TransformerCode1
Efficient data-driven gap filling of satellite image time series using deep neural networks with partial convolutionsCode1
Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood RiskCode1
Feature-Based Time-Series Analysis in R using the theft PackageCode1
TSInterpret: A unified framework for time series interpretabilityCode1
Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic ForecastingCode1
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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