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 651700 of 6748 papers

TitleStatusHype
Construe: a software solution for the explanation-based interpretation of time seriesCode1
Few-Shot Forecasting of Time-Series with Heterogeneous ChannelsCode1
Machine Learning-Based Unbalance Detection of a Rotating Shaft Using Vibration DataCode1
Machine Learning Panel Data Regressions with Heavy-tailed Dependent Data: Theory and ApplicationCode1
FiLM: Frequency improved Legendre Memory Model for Long-term Time Series ForecastingCode1
Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data DetectionCode1
Manifold Topology Divergence: a Framework for Comparing Data ManifoldsCode1
Manifold Topology Divergence: a Framework for Comparing Data Manifolds.Code1
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential EquationsCode1
Contrastive Neural Processes for Self-Supervised LearningCode1
Contrastive Learning for Unsupervised Domain Adaptation of Time SeriesCode1
Contrast Everything: A Hierarchical Contrastive Framework for Medical Time-SeriesCode1
Convolutional Radio Modulation Recognition NetworksCode1
Random Dilated Shapelet Transform: A New Approach for Time Series ShapeletsCode1
Convolution-enhanced Evolving Attention NetworksCode1
Copula Conformal Prediction for Multi-step Time Series ForecastingCode1
Arbitrage-free neural-SDE market modelsCode1
Cost-effective Interactive Attention Learning with Neural Attention ProcessesCode1
A Synthetic Texas Power System with Time-Series Weather-Dependent Spatiotemporal ProfilesCode1
Correlated Time Series Self-Supervised Representation Learning via Spatiotemporal BootstrappingCode1
Active multi-fidelity Bayesian online changepoint detectionCode1
Federated Learning for 5G Base Station Traffic ForecastingCode1
Counterfactual Explanations for Machine Learning on Multivariate Time Series DataCode1
A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading RulesCode1
COVID-19 Data Analysis and Forecasting: Algeria and the WorldCode1
FedTADBench: Federated Time-Series Anomaly Detection BenchmarkCode1
Deep Mixed Effect Model using Gaussian Processes: A Personalized and Reliable Prediction for HealthcareCode1
Financial Time Series Data Processing for Machine LearningCode1
Feature-Based Time-Series Analysis in R using the theft PackageCode1
CRISP: A Probabilistic Model for Individual-Level COVID-19 Infection Risk Estimation Based on Contact DataCode1
Crop mapping from image time series: deep learning with multi-scale label hierarchiesCode1
A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series DataCode1
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series ImputationCode1
A Review of Graph Neural Networks and Their Applications in Power SystemsCode1
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time WarpingCode1
Self-Supervised Time Series Representation Learning via Cross Reconstruction TransformerCode1
An Accurate and Fully-Automated Ensemble Model for Weekly Time Series ForecastingCode1
Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution TestsCode1
Monash Time Series Forecasting ArchiveCode1
Monash University, UEA, UCR Time Series Extrinsic Regression ArchiveCode1
Motiflets -- Simple and Accurate Detection of Motifs in Time SeriesCode1
Motion Correction and Volumetric Reconstruction for Fetal Functional Magnetic Resonance Imaging DataCode1
MrSQM: Fast Time Series Classification with Symbolic RepresentationsCode1
MSGNN: A Spectral Graph Neural Network Based on a Novel Magnetic Signed LaplacianCode1
Data Normalization for Bilinear Structures in High-Frequency Financial Time-seriesCode1
ASTRIDE: Adaptive Symbolization for Time Series DatabasesCode1
Are we certain it's anomalous?Code1
Dataset: Impact Events for Structural Health Monitoring of a Plastic Thin PlateCode1
ARMA Cell: A Modular and Effective Approach for Neural Autoregressive ModelingCode1
An Empirical Study of Graph-Based Approaches for Semi-Supervised Time Series ClassificationCode1
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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