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 4826–4850 of 6748 papers

TitleStatusHype
MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data—0
Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN)—0
Mixture Models for the Analysis, Edition, and Synthesis of Continuous Time Series—0
MLAT: Metric Learning for kNN in Streaming Time Series—0
MLFriend: Interactive Prediction Task Recommendation for Event-Driven Time-Series Data—0
Mobile Mapping Mesh Change Detection and Update—0
Mod-DeepESN: Modular Deep Echo State Network—0
On Robustness of Principal Component Regression—0
Model-Attentive Ensemble Learning for Sequence Modeling—0
Model-Based Clustering and Classification of Functional Data—0
Model-based clustering and segmentation of time series with changes in regime—0
Model-based clustering with Hidden Markov Model regression for time series with regime changes—0
Model-Based Reinforcement Learning via Stochastic Hybrid Models—0
Model-Based Reinforcement Learning for Type 1Diabetes Blood Glucose Control—0
Model-Coupled Autoencoder for Time Series Visualisation—0
Model Extraction Attacks against Recurrent Neural Networks—0
Model-free inference of unseen attractors: Reconstructing phase space features from a single noisy trajectory using reservoir computing—0
Model-free prediction of emergence of extreme events in a parametrically driven nonlinear dynamical system by Deep Learning—0
Model-free prediction of noisy chaotic time series by deep learning—0
Model identification for ARMA time series through convolutional neural networks—0
Model inference for Ordinary Differential Equations by parametric polynomial kernel regression—0
Modeling and forecasting Spread of COVID-19 epidemic in Iran until Sep 22, 2021, based on deep learning—0
Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN—0
Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants—0
Modeling biological networks: from single gene systems to large microbial communities—0
Show:102550
← PrevPage 194 of 270Next →
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