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 2301–2325 of 6748 papers

TitleStatusHype
Airflow recovery from thoracic and abdominal movements using Synchrosqueezing Transform and Locally Stationary Gaussian Process Regression—0
Chaotic Variational Auto encoder-based Adversarial Machine Learning—0
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks—0
A One-Class Support Vector Machine Calibration Method for Time Series Change Point Detection—0
Chaotic Neuronal Oscillations in Spontaneous Cortical-Subcortical Networks—0
Chaos may enhance expressivity in cerebellar granular layer—0
AimTS: Augmented Series and Image Contrastive Learning for Time Series Classification—0
Adaptive exponential power distribution with moving estimator for nonstationary time series—0
Evolution of Covariance Functions for Gaussian Process Regression using Genetic Programming—0
Exact Mean Computation in Dynamic Time Warping Spaces—0
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing—0
Chaos in Fractionally Integrated Generalized Autoregressive Conditional Heteroskedastic Processes—0
"Chaos" in energy and commodity markets: a controversial matter—0
Channel masking for multivariate time series shapelets—0
An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples—0
AI Modelling and Time-series Forecasting Systems for Trading Energy Flexibility in Distribution Grids—0
Channel-Based Attention for LCC Using Sentinel-2 Time Series—0
An Unsupervised Clustering-Based Short-Term Solar Forecasting Methodology Using Multi-Model Machine Learning Blending—0
Change Point Detection via Multivariate Singular Spectrum Analysis—0
An Unsupervised Approach for Automatic Activity Recognition based on Hidden Markov Model Regression—0
AI for trading strategies—0
Adaptive Estimation of Graphical Models under Total Positivity—0
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputation—0
AI enabled RPM for Mental Health Facility—0
Evidence and Behaviour of Support and Resistance Levels in Financial Time Series—0
Show:102550
← PrevPage 93 of 270Next →
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