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 426–450 of 6748 papers

TitleStatusHype
An efficient aggregation method for the symbolic representation of temporal dataCode1
Conformal Time-series ForecastingCode1
Conformal prediction set for time-seriesCode1
Improving S&P stock prediction with time series stock similarityCode1
Inductive Graph Neural Networks for Spatiotemporal KrigingCode1
Construe: a software solution for the explanation-based interpretation of time seriesCode1
Contrastive Neural Processes for Self-Supervised LearningCode1
An empirical evaluation of attention-based multi-head models for improved turbofan engine remaining useful life predictionCode1
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence ModelingCode1
Interpretable Models for Granger Causality Using Self-explaining Neural NetworksCode1
Interpretable Multivariate Time Series Forecasting with Temporal Attention Convolutional Neural NetworksCode1
An Empirical Evaluation of Time-Series Feature SetsCode1
Advancing the State-of-the-Art for ECG Analysis through Structured State Space ModelsCode1
An Empirical Framework for Domain Generalization in Clinical SettingsCode1
Continual Transformers: Redundancy-Free Attention for Online InferenceCode1
Continuous Latent Process FlowsCode1
Evaluation of post-hoc interpretability methods in time-series classificationCode1
Differentiable Divergences Between Time SeriesCode1
An Empirical Survey of Data Augmentation for Time Series Classification with Neural NetworksCode1
An End-to-end Deep Reinforcement Learning Approach for the Long-term Short-term Planning on the Frenet SpaceCode1
Continuous-Time Deep Glioma Growth ModelsCode1
Are we certain it's anomalous?Code1
ARMA Cell: A Modular and Effective Approach for Neural Autoregressive ModelingCode1
Adversarial Attacks on Time SeriesCode1
Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence CaseCode1
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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