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 6701–6725 of 6748 papers

TitleStatusHype
Forecastable Component Analysis (ForeCA)—0
Evaluating Hebbian Self-Organizing Memories for Lexical Representation and Access—0
PAMOCAT: Automatic retrieval of specified postures—0
Multiple Change Point Estimation in Stationary Ergodic Time Series—0
Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes—0
Change-Point Detection in Time-Series Data by Relative Density-Ratio EstimationCode0
Variational Gaussian Process Dynamical Systems—0
Learning Auto-regressive Models from Sequence and Non-sequence Data—0
A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition—0
The Influence of Global Constraints on Similarity Measures for Time-Series Databases—0
Rademacher complexity of stationary sequences—0
Forecasting Time Series With Complex Seasonal Patterns Using Exponential SmoothingCode0
Nextplace: a spatio-temporal prediction framework for pervasive systems—0
Inter-time segment information sharing for non-homogeneous dynamic Bayesian networks—0
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference—0
Identifying Patients at Risk of Major Adverse Cardiovascular Events Using Symbolic Mismatch—0
Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models—0
Movement extraction by detecting dynamics switches and repetitions—0
Twitter mood predicts the stock marketCode0
The tourism forecasting competition—0
On Recursive Edit Distance Kernels with Application to Time Series Classification—0
Estimación del Exponente de Hurst en Flujos de Tráfico Autosimilares—0
On the LRD of the Aggregated Traffic Flows in High-Speed Computer Networks—0
Traffic Flows Analysis in High-Speed Computer Networks Using Time Series—0
Canonical Time Warping for Alignment of Human Behavior—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