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 3751–3775 of 6748 papers

TitleStatusHype
The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario—0
Evolutionary Dynamics of Investors Expectations and Market Price Movement—0
The dynamics of the stomatognathic system from 4D multimodal data—0
The Dynamic Triple Gamma Prior as a Shrinkage Process Prior for Time-Varying Parameter Models—0
The Economic Impact of Critical National Infrastructure Failure Due to Space Weather—0
The Effectiveness of Discretization in Forecasting: An Empirical Study on Neural Time Series Models—0
The elastic origins of tail asymmetry—0
The Expressive Power of Gated Recurrent Units as a Continuous Dynamical System—0
The Expressivity and Training of Deep Neural Networks: toward the Edge of Chaos?—0
The Forecasting performance of the Factor model with Martingale Difference errors—0
The fractal time growth of COVID-19 pandemic: an accurate self-similar model, and urgent conclusions—0
The FreshPRINCE: A Simple Transformation Based Pipeline Time Series Classifier—0
The Functional Wiener Filter—0
The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms. Extended Version—0
The Impact of COVID-19 on FinTech Lending in Indonesia: Evidence From Interrupted Time Series Analysis—0
The Importance of Being Correlated: Implications of Dependence in Joint Spectral Inference across Multiple Networks—0
The Influence of Global Constraints on Similarity Measures for Time-Series Databases—0
The Internet of Things as a Deep Neural Network—0
The interpretation of endobronchial ultrasound image using 3D convolutional neural network for differentiating malignant and benign mediastinal lesions—0
The (in)visible hand in the Libor market: an Information Theory approach—0
The Kernel Trick for Nonlinear Factor Modeling—0
The Lifecycle of a Statistical Model: Model Failure Detection, Identification, and Refitting—0
The Local to Unity Dynamic Tobit Model—0
Market-Based Asset Price Probability—0
Market-Based Probability of Stock Returns—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