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 6051–6075 of 6748 papers

TitleStatusHype
Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modelingCode0
Learning from the past, predicting the statistics for the future, learning an evolving systemCode0
On the Reconstruction Risk of Convolutional Sparse Dictionary LearningCode0
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series DataCode0
The UEA multivariate time series classification archive, 2018Code0
Global Models for Time Series Forecasting: A Simulation StudyCode0
Gesture Recognition in RGB Videos UsingHuman Body Keypoints and Dynamic Time WarpingCode0
Benchmarking optimality of time series classification methods in distinguishing diffusionsCode0
On the separation of shape and temporal patterns in time series -Application to signature authentication-Code0
Twitter mood predicts the stock marketCode0
On the Soundness of XAI in Prognostics and Health Management (PHM)Code0
An ensemble neural network approach to forecast Dengue outbreak based on climatic conditionCode0
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation modelCode0
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based PerspectiveCode0
Learning interaction rules from multi-animal trajectories via augmented behavioral modelsCode0
ST-LSTM: A Deep Learning Approach Combined Spatio-Temporal Features for Short-TermCode0
The Utility of Hyperplane Angle Metric in Detecting Financial Concept DriftCode0
Toward Asymptotic Optimality: Sequential Unsupervised Regression of Density Ratio for Early ClassificationCode0
Identifying Latent Stochastic Differential EquationsCode0
Stochastic embeddings of dynamical phenomena through variational autoencodersCode0
Geodesic Density Regression for Correcting 4DCT Pulmonary Respiratory Motion ArtifactsCode0
Robust Lane Detection from Continuous Driving Scenes Using Deep Neural NetworksCode0
Generative Optimization Networks for Memory Efficient Data GenerationCode0
Learning low-frequency temporal patterns for quantitative tradingCode0
Stochastic Gradient MCMC for Nonlinear State Space ModelsCode0
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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