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 6551–6575 of 6748 papers

TitleStatusHype
Multiple Output Regression with Latent Noise—0
Initialization of multilayer forecasting artifical neural networks—0
Graphical LASSO Based Model Selection for Time Series—0
Training Algorithm for Neuro-Fuzzy Network Based on Singular Spectrum Analysis—0
Financial Keyword Expansion via Continuous Word Vector Representations—0
Exploiting Social Relations and Sentiment for Stock Prediction—0
Efficient multivariate sequence classification—0
When Darwin meets Lorenz: Evolving new chaotic attractors through genetic programming—0
Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study—0
Metric Learning for Temporal Sequence Alignment—0
A Wild Bootstrap for Degenerate Kernel TestsCode0
Multi-Sensor Event Detection using Shape Histograms—0
Automated Machine Learning on Big Data using Stochastic Algorithm Tuning—0
Dissimilarity-based Sparse Subset Selection—0
Deep Recurrent Neural Networks for Time Series Prediction—0
One-Step or Two-Step Optimization and the Overfitting Phenomenon: A Case Study on Time Series Classification—0
A Framework for Exploring Non-Linear Functional Connectivity and Causality in the Human Brain: Mutual Connectivity Analysis (MCA) of Resting-State Functional MRI with Convergent Cross-Mapping and Non-Metric Clustering—0
Finding Motif Sets in Time Series—0
Identifying Cover Songs Using Information-Theoretic Measures of Similarity—0
Meteorological time series forecasting with pruned multi-layer perceptron and 2-stage Levenberg-Marquardt method—0
Techniques for clustering interaction data as a collection of graphs—0
Early Recognition of Human Activities from First-Person Videos Using Onset Representations—0
Variational Gaussian Process State-Space Models—0
An Experimental Evaluation of Nearest Neighbour Time Series Classification—0
Interval Forecasting of Electricity Demand: A Novel Bivariate EMD-based Support Vector Regression Modeling Framework—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