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 251–275 of 6748 papers

TitleStatusHype
Probabilistic Decomposition Transformer for Time Series 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
A Large-Scale Annotated Multivariate Time Series Aviation Maintenance Dataset from the NGAFIDCode1
Empirical Evaluation of Data Augmentations for Biobehavioral Time Series Data with Deep LearningCode1
Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series ForecastingCode1
Deep Counterfactual Estimation with Categorical Background VariablesCode1
Transformer-based conditional generative adversarial network for multivariate time series generationCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
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
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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