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

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Showing 2401–2450 of 6748 papers

TitleStatusHype
Estimating Task Completion Times for Network Rollouts using Statistical Models within Partitioning-based Regression Methods—0
Estimating the Algorithmic Complexity of Stock Markets—0
Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach—0
Change of persistence in European electricity spot prices—0
Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series—0
Estimating Treatment Effects in Continuous Time with Hidden Confounders—0
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders—0
Estimating value at risk: LSTM vs. GARCH—0
Anticipating synchronization with machine learning—0
Ensembles of Randomized NNs for Pattern-based Time Series Forecasting—0
Estimation and Quantization of Expected Persistence Diagrams—0
Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations—0
Application of Machine Learning to accidents detection at directional drilling—0
Estimation of Cross-Sectional Dependence in Large Panels—0
Estimation of Evaporator Valve Sizes in Supermarket Refrigeration Cabinets—0
Estimation of High-Dimensional Markov-Switching VAR Models with an Approximate EM Algorithm—0
Change Point Detection via Multivariate Singular Spectrum Analysis—0
Estimation of multivariate asymmetric power GARCH models—0
A Novel Multi-Stage Training Approach for Human Activity Recognition from Multimodal Wearable Sensor Data Using Deep Neural Network—0
Estimation of Shade Losses in Unlabeled PV Data—0
Channel-Based Attention for LCC Using Sentinel-2 Time Series—0
Estimation of the mortality rate functions from time series field data in a stage-structured demographic model for Lobesia botrana—0
Ethereum Price Prediction Employing Large Language Models for Short-term and Few-shot Forecasting—0
Causal Triple Attention Time Series Forecasting—0
A Hybrid Distribution Feeder Long-Term Load Forecasting Method Based on Sequence Prediction—0
Ensemble of Hankel Matrices for Face Emotion Recognition—0
EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid—0
Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions—0
Evaluating conditional covariance estimates via a new targeting approach and a networks-based analysis—0
Evaluating Contrastive Learning on Wearable Timeseries for Downstream Clinical Outcomes—0
Fading of collective attention shapes the evolution of linguistic variants—0
Fairness in Forecasting and Learning Linear Dynamical Systems—0
Chaotic Neuronal Oscillations in Spontaneous Cortical-Subcortical Networks—0
Evaluating genetic drift in time-series evolutionary analysis—0
Ensemble neuroevolution based approach for multivariate time series anomaly detection—0
Chaotic Time Series Prediction using Spatio-Temporal RBF Neural Networks—0
Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark—0
Evaluating Machine Learning Models for the Fast Identification of Contingency Cases—0
Ensemble manifold based regularized multi-modal graph convolutional network for cognitive ability prediction—0
Characterization of catastrophic instabilities: Market crashes as paradigm—0
Causal Structural Learning from Time Series: A Convex Optimization Approach—0
Characterization of causal ancestral graphs for time series with latent confounders—0
Ensemble Grammar Induction For Detecting Anomalies in Time Series—0
Characterization of electric consumers through an automated clustering pipeline—0
Evaluating the Performance of ANN Prediction System at Shanghai Stock Market in the Period 21-Sep-2016 to 11-Oct-2016—0
Evaluating the Robustness of Time Series Anomaly and Intrusion Detection Methods against Adversarial Attacks—0
Characterizing the Emotion Carriers of COVID-19 Misinformation and Their Impact on Vaccination Outcomes in India and the United States—0
Evaluation and Ensembling of Methods for Reverse Engineering of Brain Connectivity from Imaging Data—0
A Novel Multi-Centroid Template Matching Algorithm and Its Application to Cough Detection—0
Adaptive Complementary Ensemble EMD and Energy-Frequency Spectra of Cryptocurrency Prices—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