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 2126–2150 of 6748 papers

TitleStatusHype
NLP Based Anomaly Detection for Categorical Time Series—0
Causal Analysis of Generic Time Series Data Applied for Market Prediction—0
Dirichlet Proportions Model for Hierarchically Coherent Probabilistic Forecasting—0
Learning Sequential Latent Variable Models from Multimodal Time Series DataCode0
A data filling methodology for time series based on CNN and (Bi)LSTM neural networks—0
Changepoint Detection in Noisy Data Using a Novel Residuals Permutation-Based Method (RESPERM): Benchmarking and Application to Single Trial ERPsCode0
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features—0
A Convolutional-Attentional Neural Framework for Structure-Aware Performance-Score Synchronization—0
EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting—0
LORD: Lower-Dimensional Embedding of Log-Signature in Neural Rough Differential EquationsCode0
Benign Overfitting in Time Series Linear Models with Over-Parameterization—0
Multi-scale Anomaly Detection for Big Time Series of Industrial Sensors—0
An advanced spatio-temporal convolutional recurrent neural network for storm surge predictions—0
STONet: A Neural-Operator-Driven Spatio-temporal Network—0
Time Series Clustering for Grouping Products Based on Price and Sales Patterns—0
Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach—0
Assessing Differentially Private Variational Autoencoders under Membership InferenceCode0
Nonparametric Analysis of Dynamic Random Utility Models—0
Learning Probability Distributions in Macroeconomics and Finance—0
Time Series of Non-Additive Metrics: Identification and Interpretation of Contributing Factors of Variance by Linear Decomposition—0
Stability of China's Stock Market: Measure and Forecast by Ricci Curvature on Network—0
EvoSTS Forecasting: Evolutionary Sparse Time-Series Forecasting—0
Neural Topic Modeling of Psychotherapy Sessions—0
Investigating Temporal Convolutional Neural Networks for Satellite Image Time Series Classification: A survey—0
Features of the Earth's seasonal hydroclimate: Characterizations and comparisons across the Koppen-Geiger climates and across continents—0
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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