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

Showing 63016350 of 6748 papers

TitleStatusHype
Segmenting Hybrid Trajectories using Latent ODEsCode0
XceptionTime: A Novel Deep Architecture based on Depthwise Separable Convolutions for Hand Gesture ClassificationCode0
Wasserstein Index Generation Model: Automatic Generation of Time-series Index with Application to Economic Policy UncertaintyCode0
Few-shot human motion prediction for heterogeneous sensorsCode0
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance MatricesCode0
Towards Safe Policy Improvement for Non-Stationary MDPsCode0
fETSmcs: Feature-based ETS model component selectionCode0
Machine Learning vs Statistical Methods for Time Series Forecasting: Size MattersCode0
PI-Net: A Deep Learning Approach to Extract Topological Persistence ImagesCode0
Conditional Latent Block Model: a Multivariate Time Series Clustering Approach for Autonomous Driving ValidationCode0
Analysis of Thai Capital Market Linkages: Part I. Bivariate Copula ApproachCode0
Deep Normed Embeddings for Patient RepresentationCode0
A projected nonlinear state-space model for forecasting time series signalsCode0
MAD-GAN: Multivariate Anomaly Detection for Time Series Data with Generative Adversarial NetworksCode0
Feature space approximation for kernel-based supervised learningCode0
Feature Selection on a Flare Forecasting Testbed: A Comparative Study of 24 MethodsCode0
MAGMA: Inference and Prediction with Multi-Task Gaussian ProcessesCode0
Wasserstein multivariate auto-regressive models for modeling distributional time seriesCode0
PMP: Privacy-Aware Matrix Profile against Sensitive Pattern Inference for Time SeriesCode0
Self-attention for raw optical Satellite Time Series ClassificationCode0
Feature Selection for Multivariate Time Series via Network PruningCode0
Feature engineering workflow for activity recognition from synchronized inertial measurement unitsCode0
Autoregressive Convolutional Neural Networks for Asynchronous Time SeriesCode0
Manifold Oblique Random Forests: Towards Closing the Gap on Convolutional Deep NetworksCode0
Policy Analysis using Synthetic Controls in Continuous-TimeCode0
Manifold-regression to predict from MEG/EEG brain signals without source modelingCode0
Fast Online Deconvolution of Calcium Imaging DataCode0
Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEsCode0
Switching Autoregressive Low-rank Tensor ModelsCode0
A Probabilistic Autoencoder for Type Ia Supernovae Spectral Time SeriesCode0
Pooled Motion Features for First-Person VideosCode0
POP: Mining POtential Performance of new fashion products via webly cross-modal query expansionCode0
Self-explaining Hierarchical Model for Intraoperative Time SeriesCode0
Automatic alignment of surgical videos using kinematic dataCode0
AdaVol: An Adaptive Recursive Volatility Prediction MethodCode0
Approximating Continuous Functions on Persistence Diagrams Using Template FunctionsCode0
Fast fitting of neural ordinary differential equations by Bayesian neural gradient matching to infer ecological interactions from time series dataCode0
Fast ES-RNN: A GPU Implementation of the ES-RNN AlgorithmCode0
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented PopulationsCode0
Deep Neural Network Ensembles for Time Series ClassificationCode0
Conditional Approximate Normalizing Flows for Joint Multi-Step Probabilistic Forecasting with Application to Electricity DemandCode0
Concept-based model explanations for Electronic Health RecordsCode0
Deep Multi-View Spatial-Temporal Network for Taxi Demand PredictionCode0
An accuracy-runtime trade-off comparison of scalable Gaussian process approximations for spatial dataCode0
A clustering approach to time series forecasting using neural networks: A comparative study on distance-based vs. feature-based clustering methodsCode0
Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random FeaturesCode0
Approximate Bayesian Computation with Path SignaturesCode0
Faster Retrieval with a Two-Pass Dynamic-Time-Warping Lower BoundCode0
VELC: A New Variational AutoEncoder Based Model for Time Series Anomaly DetectionCode0
Self-supervised representation learning from electroencephalography signalsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1naive classifierF187.47Unverified
2GRU-D - APC (n = 1)F127.3Unverified
3GRU-APC (n = 1)F125.7Unverified
4GRU-DF122.5Unverified
5GRUF122.3Unverified
6GRU-SimpleF122.2Unverified
7GRU-MeanF122.1Unverified
#ModelMetricClaimedVerifiedStatus
1SepTr% Test Accuracy98.51Unverified
2ViT% Test Accuracy98.11Unverified
3FlexTCN-4% Test Accuracy97.73Unverified
4MatchboxNet% Test Accuracy97.4Unverified
5CKCNN (100k)% Test Accuracy95.27Unverified
6FlexTCN-6% Test Accuracy (Raw Data)91.73Unverified
#ModelMetricClaimedVerifiedStatus
1ResBiLSTMMAE0.13Unverified