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 4401–4425 of 6748 papers

TitleStatusHype
Interpretable System Identification and Long-term Prediction on Time-Series Data—0
Interpretable Time Series Clustering Using Local Explanations—0
Learning Disentangled Representations for Time Series—0
Interpretable Water Level Forecaster with Spatiotemporal Causal Attention Mechanisms—0
Interpretable Vector AutoRegressions with Exogenous Time Series—0
Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution—0
Interpreting a Recurrent Neural Network's Predictions of ICU Mortality Risk—0
Interpreting intermediate convolutional layers of generative CNNs trained on waveforms—0
Interpreting intermediate convolutional layers in unsupervised acoustic word classification—0
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks—0
Interval Forecasting of Electricity Demand: A Novel Bivariate EMD-based Support Vector Regression Modeling Framework—0
Intra-day Activity Better Predicts Chronic Conditions—0
Intraday Functional PCA Forecasting of Cryptocurrency Returns—0
Intraday trading strategy based on time series and machine learning for Chinese stock market—0
Intra-domain and cross-domain transfer learning for time series data -- How transferable are the features?—0
Intrinsic Anomaly Detection for Multi-Variate Time Series—0
Introducing Data Primitives: Data Formats for the SKED Framework—0
Introducing Randomized High Order Fuzzy Cognitive Maps as Reservoir Computing Models: A Case Study in Solar Energy and Load Forecasting—0
Market-Based Price Autocorrelation—0
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems—0
Invariant Factorization Of Time-Series—0
Invariants of multidimensional time series based on their iterated-integral signature—0
Long Short-Term Memory Neural Networks for False Information Attack Detection in Software-Defined In-Vehicle Network—0
Inverse Moment Methods for Sufficient Forecasting using High-Dimensional Predictors—0
Inverse and Quanto Inverse Options in a Black-Scholes World—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