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 1376–1400 of 6748 papers

TitleStatusHype
Spectral Cross-Domain Neural Network with Soft-adaptive Threshold Spectral EnhancementCode0
On Consistency and Asymptotic Normality of Least Absolute Deviation Estimators for 2-dimensional Sinusoidal Model—0
On the Susceptibility and Robustness of Time Series Models through Adversarial Attack and Defense—0
Machine Learning Applied to Peruvian Vegetables Imports—0
Quantile Autoregression-based Non-causality Testing—0
A Robust Data-driven Process Modeling Applied to Time-series Stochastic Power Flow—0
DANLIP: Deep Autoregressive Networks for Locally Interpretable Probabilistic Forecasting—0
Recursive classification of satellite imaging time-series: An application to land cover mappingCode0
Graph state-space models—0
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time SeriesCode0
Infomaxformer: Maximum Entropy Transformer for Long Time-Series Forecasting Problem—0
Towards Explainable Land Cover Mapping: a Counterfactual-based Strategy—0
Identifying Exoplanets with Deep Learning. V. Improved Light Curve Classification for TESS Full Frame Image ObservationsCode0
Covariate-guided Bayesian mixture model for multivariate time seriesCode0
Common patterns between dengue cases, climate, and local environmental variables in Costa Rica: A Wavelet Approach—0
Neural SDEs for Conditional Time Series Generation and the Signature-Wasserstein-1 metricCode0
Explicitly Solvable Continuous-time Inference for Partially Observed Markov Processes—0
Point Cloud-based Proactive Link Quality Prediction for Millimeter-wave Communications—0
Non-intrusive Water Usage Classification Considering Limited Training Data—0
Efficient Online Learning with Memory via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control—0
Russia-Ukraine war: Modeling and Clustering the Sentiments Trends of Various Countries—0
Unleashing the Power of Shared Label Structures for Human Activity Recognition—0
A plug-in graph neural network to boost temporal sensitivity in fMRI analysis—0
A Functional approach for Two Way Dimension Reduction in Time Series—0
Inference on Time Series Nonparametric Conditional Moment Restrictions Using General Sieves—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