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 6626–6650 of 6748 papers

TitleStatusHype
Invariant Factorization Of Time-Series—0
Classifiers With a Reject Option for Early Time-Series Classification—0
Particle Swarm Optimization of Information-Content Weighting of Symbolic Aggregate Approximation—0
Causal Inference on Time Series using Restricted Structural Equation Models—0
Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators.—0
Locally Adaptive Bayesian Multivariate Time Series—0
Training and Analysing Deep Recurrent Neural Networks—0
Sparse nonnegative deconvolution for compressive calcium imaging: algorithms and phase transitions—0
Multilinear Dynamical Systems for Tensor Time Series—0
雜訊環境下應用線性估測編碼於特徵時序列之強健性語音辨識 (Employing Linear Prediction Coding in Feature Time Sequences for Robust Speech Recognition in Noisy Environments) [In Chinese]—0
Sparse Linear Dynamical System with Its Application in Multivariate Clinical Time Series—0
Universal Codes from Switching Strategies—0
A Unified SVM Framework for Signal Estimation—0
A Visibility Graph Averaging Aggregation Operator—0
Compressive Nonparametric Graphical Model Selection For Time Series—0
Constructing Time Series Shape Association Measures: Minkowski Distance and Data Standardization—0
Joint Estimation of Multiple Graphical Models from High Dimensional Time Series—0
Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series—0
Time Series Topic Modeling and Bursty Topic Detection of Correlated News and Twitter—0
Cross-Recurrence Quantification Analysis of Categorical and Continuous Time Series: an R package—0
Observing Features of PTT Neologisms: A Corpus-driven Study with N-gram Model—0
How Noisy Social Media Text, How Diffrnt Social Media Sources?—0
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection—0
Mixed Membership Models for Time Series—0
Temporal Autoencoding Improves Generative Models of Time Series—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