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 2101–2150 of 6748 papers

TitleStatusHype
Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC—0
An Improved Multi-Output Gaussian Process RNN with Real-Time Validation for Early Sepsis Detection—0
A Fast-Optimal Guaranteed Algorithm For Learning Sub-Interval Relationships in Time Series—0
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting—0
Detecting correlations and triangular arbitrage opportunities in the Forex by means of multifractal detrended cross-correlations analysis—0
Bayesian Filtering for Multi-period Mean-Variance Portfolio Selection—0
Detecting Concrete Abnormality Using Time-series Thermal Imaging and Supervised Learning—0
Detecting Changes in Twitter Streams using Temporal Clusters of Hashtags—0
Bayesian Convolutional Deep Sets with Task-Dependent Stationary Prior—0
An Improved Mathematical Model of Sepsis: Modeling, Bifurcation Analysis, and Optimal Control Study for Complex Nonlinear Infectious Disease System—0
Detecting changes in slope with an L_0 penalty—0
Detecting Change in Seasonal Pattern via Autoencoder and Temporal Regularization—0
Bayesian Bilinear Neural Network for Predicting the Mid-price Dynamics in Limit-Order Book Markets—0
Detecting CAN Masquerade Attacks with Signal Clustering Similarity—0
Detecting British Columbia Coastal Rainfall Patterns by Clustering Gaussian Processes—0
Bayesian autoregressive spectral estimation—0
An improved LogNNet classifier for IoT application—0
A fast noise filtering algorithm for time series prediction using recurrent neural networks—0
Detecting Attacks on IoT Devices using Featureless 1D-CNN—0
Detecting a trend change in cross-border epidemic transmission—0
Bayesian Alignments of Warped Multi-Output Gaussian Processes—0
Detecting and modelling delayed density-dependence in abundance time series of a small mammal (Didelphis aurita)—0
Impulse data models for the inverse problem of electrocardiography—0
Animal behavior classification via deep learning on embedded systems—0
Locating line and node disturbances in networks of diffusively coupled dynamical agents—0
Detecting and explaining changes in various assets' relationships in financial markets—0
Basic Filters for Convolutional Neural Networks Applied to Music: Training or Design?—0
DETECT: A Hierarchical Clustering Algorithm for Behavioural Trends in Temporal Educational Data—0
Bandwidth-efficient distributed neural network architectures with application to body sensor networks—0
Animal Behavior Classification via Accelerometry Data and Recurrent Neural Networks—0
A Fast Evidential Approach for Stock Forecasting—0
Deteção de estruturas permanentes a partir de dados de séries temporais Sentinel 1 e 2—0
Detailed Primary and Secondary Distribution System Model Enhancement Using AMI Data—0
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition—0
DeStress: Deep Learning for Unsupervised Identification of Mental Stress in Firefighters from Heart-rate Variability (HRV) Data—0
Design-time Fashion Popularity Forecasting in VR Environments—0
Bag of Recurrence Patterns Representation for Time-Series Classification—0
Characterizing the memory capacity of transmon qubit reservoirs—0
Deriving land surface phenology indicators from CO2 eddy covariance measurements—0
ANFIS-based prediction of power generation for combined cycle power plant—0
Depth Evaluation for Metal Surface Defects by Eddy Current Testing using Deep Residual Convolutional Neural Networks—0
Depression Diagnosis and Drug Response Prediction via Recurrent Neural Networks and Transformers Utilizing EEG Signals—0
Backpropagation on Dynamical Networks—0
Dependent Matérn Processes for Multivariate Time Series—0
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks—0
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective—0
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification—0
Denoising Time Series Data Using Asymmetric Generative Adversarial Networks—0
Denoising neural networks for magnetic resonance spectroscopy—0
Backdoor Attacks against Transfer Learning with Pre-trained Deep Learning Models—0
Show:102550
← PrevPage 43 of 135Next →
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