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 6426–6450 of 6748 papers

TitleStatusHype
Deep Learning for MusicCode0
Automatic Segmentation of the Placenta in BOLD MRI Time SeriesCode0
Automatic Health Problem Detection from Gait Videos Using Deep Neural NetworksCode0
Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series PredictionCode0
Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flowCode0
Bubble Prediction of Non-Fungible Tokens (NFTs): An Empirical InvestigationCode0
Automatic Construction and Natural-Language Description of Nonparametric Regression ModelsCode0
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in HealthcareCode0
Predicting the impact of treatments over time with uncertainty aware neural differential equationsCode0
Experimental Study on Time Series Analysis of Lower Limb Rehabilitation Exercise Data Driven by Novel Model Architecture and Large ModelsCode0
Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team ScenarioCode0
Predicting the Number of Reported Bugs in a Software RepositoryCode0
Experimental study of time series forecasting methods for groundwater level predictionCode0
Tailoring Artificial Neural Networks for Optimal LearningCode0
Predicting the Stability of Hierarchical Triple Systems with Convolutional Neural NetworksCode0
A Complex Systems Approach To Feature Extraction for Chaotic Behavior RecognitionCode0
Sequential Gaussian Processes for Online Learning of Nonstationary FunctionsCode0
Exoplanet Detection using Machine LearningCode0
Taking ROCKET on an Efficiency Mission: Multivariate Time Series Classification with LightWaveSCode0
Mixture-based Multiple Imputation Model for Clinical Data with a Temporal DimensionCode0
Clustering Noisy Signals with Structured Sparsity Using Time-Frequency RepresentationCode0
Time Series Clustering via Community Detection in NetworksCode0
Mixture of Input-Output Hidden Markov Models for Heterogeneous Disease Progression ModelingCode0
Time Series Clustering with an EM algorithm for Mixtures of Linear Gaussian State Space ModelsCode0
ML-Based Approach for NFL Defensive Pass Interference Prediction Using GPS Tracking DataCode0
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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