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 5851–5875 of 6748 papers

TitleStatusHype
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula ProcessesCode0
A Bayesian-inspired, deep learning-based, semi-supervised domain adaptation technique for land cover mappingCode0
Non-Stationary Spectral KernelsCode0
Distributed and parallel time series feature extraction for industrial big data applicationsCode0
Distillation Enhanced Time Series Forecasting Network with Momentum Contrastive LearningCode0
Regime recovery using implied volatility in Markov modulated market modelCode0
BLEND: Behavior-guided Neural Population Dynamics Modeling via Privileged Knowledge DistillationCode0
Tropical time series, iterated-sums signatures and quasisymmetric functionsCode0
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOpsCode0
Introducing Block-Toeplitz Covariance Matrices to Remaster Linear Discriminant Analysis for Event-related Potential Brain-computer InterfacesCode0
TrueSkill Through Time: Revisiting the History of ChessCode0
Spatio-Temporal Stability Analysis in Satellite Image Times SeriesCode0
Accurate Inference for Adaptive Linear ModelsCode0
An Infra-Structure for Performance Estimation and Experimental Comparison of Predictive Models in RCode0
Black box variational inference for state space modelsCode0
Not to Cry Wolf: Distantly Supervised Multitask Learning in Critical CareCode0
Specific Differential Entropy Rate Estimation for Continuous-Valued Time SeriesCode0
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing FlowsCode0
Cross-modal Knowledge Distillation for Vision-to-Sensor Action RecognitionCode0
Hierarchical Probabilistic Model for Blind Source Separation via Legendre TransformationCode0
A Knowledge Distillation Ensemble Framework for Predicting Short and Long-term Hospitalisation Outcomes from Electronic Health Records DataCode0
Investigating Enhancements to Contrastive Predictive Coding for Human Activity RecognitionCode0
Investigating Recurrent Neural Network Memory Structures using Neuro-EvolutionCode0
Regulating Greed Over Time in Multi-Armed BanditsCode0
Bioluminescence modeling for deep sea experimentsCode0
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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