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 2451–2475 of 6748 papers

TitleStatusHype
Reservoir Computing with Diverse Timescales for Prediction of Multiscale Dynamics—0
Deep Sequence Modeling: Development and Applications in Asset Pricing—0
ASAT: Adaptively Scaled Adversarial Training in Time Series—0
DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic PredictionCode1
Feature-weighted Stacking for Nonseasonal Time Series Forecasts: A Case Study of the COVID-19 Epidemic Curves—0
Construction Cost Index Forecasting: A Multi-feature Fusion Approach—0
Federated Variational Learning for Anomaly Detection in Multivariate Time Series—0
XAI Methods for Neural Time Series Classification: A Brief Review—0
Stack Index Prediction Using Time-Series Analysis—0
Transformers predicting the future. Applying attention in next-frame and time series forecastingCode0
Structure Parameter Optimized Kernel Based Online Prediction with a Generalized Optimization Strategy for Nonstationary Time Series—0
AGNet: Weighing Black Holes with Deep LearningCode1
A complex network approach to time series analysis with application in diagnosis of neuromuscular disorders—0
Time delay estimation of traffic congestion propagation due to accidents based on statistical causalityCode0
Event2Graph: Event-driven Bipartite Graph for Multivariate Time-series Anomaly Detection—0
Deep Learning-based Time-varying Channel Estimation for RIS Assisted Communication—0
Data-driven discovery of intrinsic dynamicsCode1
IT2CFNN: An Interval Type-2 Correlation-Aware Fuzzy Neural Network to Construct Non-Separable Fuzzy Rules with Uncertain and Adaptive Shapes for Nonlinear Function Approximation—0
Empirical Risk Minimization for Time Series: Nonparametric Performance Bounds for Prediction—0
AdaRNN: Adaptive Learning and Forecasting of Time SeriesCode0
Completion and Augmentation based Spatiotemporal Deep Learning Approach for Short-Term Metro Origin-Destination Matrix Prediction under Limited Observable DataCode0
Ensemble neuroevolution based approach for multivariate time series anomaly detection—0
#StayHome or #Marathon? Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs—0
Active Learning of Driving Scenario Trajectories—0
Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Series—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