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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 5301–5350 of 6748 papers

TitleStatusHype
Learning Representations of Missing Data for Predicting Patient Outcomes—0
Langevin-gradient parallel tempering for Bayesian neural learningCode0
StationPlot: A New Non-stationarity Quantification Tool for Detection of Epileptic Seizures—0
EA-LSTM: Evolutionary Attention-based LSTM for Time Series Prediction—0
Benchmarking Deep Sequential Models on Volatility Predictions for Financial Time Series—0
Explainable cardiac pathology classification on cine MRI with motion characterization by semi-supervised learning of apparent flowCode0
Estimating Network Structure from Incomplete Event Data—0
Time Series Classification to Improve Poultry Welfare—0
Nonlinear Evolution via Spatially-Dependent Linear Dynamics for Electrophysiology and Calcium Data—0
Day-ahead time series forecasting: application to capacity planning—0
Towards a Near Universal Time Series Data Mining Tool: Introducing the Matrix Profile—0
Transfer learning for time series classificationCode1
Representation Learning by Reconstructing Neighborhoods—0
Theoretical and Experimental Analysis on the Generalizability of Distribution Regression Network—0
Challenges in detecting evolutionary forces in language change using diachronic corporaCode0
Data-driven Perception of Neuron Point Process with Unknown UnknownsCode0
Representation of Word Meaning in the Intermediate Projection Layer of a Neural Language Model—0
Can automated smoothing significantly improve benchmark time series classification algorithms?—0
PerceptionNet: A Deep Convolutional Neural Network for Late Sensor Fusion—0
Efficient Online Hyperparameter Optimization for Kernel Ridge Regression with Applications to Traffic Time Series Prediction—0
The UEA multivariate time series classification archive, 2018Code0
Contrastive Multivariate Singular Spectrum Analysis—0
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent statesCode0
Adaptive Extreme Learning Machine for Recurrent Beta-basis Function Neural Network Training—0
Bayesian nonparametric sparse VAR models—0
Causal Inference in Nonverbal Dyadic Communication with Relevant Interval Selection and Granger Causality—0
Semi-unsupervised Learning of Human Activity using Deep Generative ModelsCode0
Phase Harmonic Correlations and Convolutional Neural NetworksCode0
Gaussian Process Prior Variational AutoencodersCode1
Wi-Motion: A Robust Human Activity Recognition Using WiFi Signals—0
Time series clustering based on the characterisation of segment typologies—0
The CoSTAR Block Stacking Dataset: Learning with Workspace ConstraintsCode0
Deep Poisson gamma dynamical systems—0
DeepDPM: Dynamic Population Mapping via Deep Neural Network—0
Deep Learning with Long Short-Term Memory for Time Series Prediction—0
Precipitation Nowcasting: Leveraging bidirectional LSTM and 1D CNN—0
Autowarp: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders—0
Using Deep Learning for price prediction by exploiting stationary limit order book features—0
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE)—0
Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach—0
Stochastic Gradient MCMC for State Space ModelsCode0
Training Dynamic Exponential Family Models with Causal and Lateral Dependencies for Generalized Neuromorphic Computing—0
Deep multi-survey classification of variable stars—0
Study of non-linear viscoelastic behavior of the human red blood cell—0
Nonlinear methods to quantify Movement Variability in Human-Humanoid Interaction ActivitiesCode0
Deep Diabetologist: Learning to Prescribe Hyperglycemia Medications with Hierarchical Recurrent Neural Networks—0
The UCR Time Series ArchiveCode0
A Periodicity-based Parallel Time Series Prediction Algorithm in Cloud Computing Environments—0
Accounting for Unobservable Heterogeneity in Cross Section Using Spatial First Differences—0
Specific low frequency electromagnetic fields induce epigenetic and functional changes in U937 cells—0
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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