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 1901–1925 of 6748 papers

TitleStatusHype
Convolutional Neural Networks for Time-dependent Classification of Variable-length Time Series—0
Causal Discovery using Model Invariance through Knockoff InterventionsCode0
Backpropagation on Dynamical Networks—0
Semi-unsupervised Learning for Time Series ClassificationCode0
Don't overfit the history -- Recursive time series data augmentation—0
Variations on two-parameter families of forecasting functions: seasonal/nonseasonal Models, comparison to the exponential smoothing and ARIMA models, and applications to stock market data—0
Astroconformer: Inferring Surface Gravity of Stars from Stellar Light Curves with Transformer—0
Composite FORCE learning of chaotic echo state networks for time-series prediction—0
Reinforcement Learning Portfolio Manager Framework with Monte Carlo Simulation—0
Adaptive deep learning for nonlinear time series models—0
Sedentary Behavior Estimation with Hip-worn Accelerometer Data: Segmentation, Classification and Thresholding—0
Temporal Sequence Object-based CNN (TS-OCNN) for crop classification from fine resolution remote sensing image time-series—0
Modeling Randomly Walking Volatility with Chained Gamma Distributions—0
Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures—0
Input Sequence and Parameter Estimation in Impulsive Biomedical Models—0
Data-Driven Modeling of Noise Time Series with Convolutional Generative Adversarial NetworksCode0
Continuous Sign Language Recognition via Temporal Super-Resolution Network—0
Comparative Analysis of Time Series Forecasting Approaches for Household Electricity Consumption Prediction—0
Scheduling Planting Time Through Developing an Optimization Model and Analysis of Time Series Growing Degree Units—0
Simulating financial time series using attention—0
A Temporal Fusion Transformer for Long-term Explainable Prediction of Emergency Department Overcrowding—0
Rapid training of quantum recurrent neural networksCode0
Using Machine Learning to Anticipate Tipping Points and Extrapolate to Post-Tipping Dynamics of Non-Stationary Dynamical Systems—0
Stock Performance Evaluation for Portfolio Design from Different Sectors of the Indian Stock Market—0
Hierarchic Temporal Convolutional Network With Cross-Domain Encoder for Music Source Separation—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