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

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Showing 951–1000 of 6748 papers

TitleStatusHype
Review of Clustering Methods for Functional Data—0
Unsupervised Model Selection for Time-series Anomaly DetectionCode1
Combined Dynamic Virtual Spatiotemporal Graph Mapping for Traffic PredictionCode0
Improving Convolutional Neural Networks for Fault Diagnosis by Assimilating Global Features—0
Grouped self-attention mechanism for a memory-efficient Transformer—0
Fast and Robust Video-Based Exercise Classification via Body Pose Tracking and Scalable Multivariate Time Series ClassifiersCode0
Finding Scientific Topics in Continuously Growing Text CorporaCode1
Robust Trajectory-based Density Estimation for Geometric Structure Recovery: Theory and Applications—0
Solar Power Time Series Forecasting Utilising Wavelet Coefficients—0
A Sequence-Aware Recommendation Method Based on Complex Networks—0
Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised LearningCode1
A Multi-label Time Series Classification Approach for Non-intrusive Water End-Use Monitoring—0
Fast Inference for Quantile Regression with Tens of Millions of Observations—0
A case study of spatiotemporal forecasting techniques for weather forecastingCode0
Explainable classification of astronomical uncertain time series—0
Towards Automatic Forecasting: Evaluation of Time-Series Forecasting Models for Chickenpox Cases Estimation in Hungary—0
Masked Multi-Step Multivariate Time Series Forecasting with Future Information—0
Happy or grumpy? A Machine Learning Approach to Analyze the Sentiment of Airline Passengers' Tweets—0
Experimental study of time series forecasting methods for groundwater level predictionCode0
Non-contrastive representation learning for intervals from well logs—0
Active Transfer Prototypical Network: An Efficient Labeling Algorithm for Time-Series Data—0
Retrieval Based Time Series Forecasting—0
Neural parameter calibration for large-scale multi-agent modelsCode1
Predicting Swarm Equatorial Plasma Bubbles via Machine Learning and Shapley Values—0
DynImp: Dynamic Imputation for Wearable Sensing Data Through Sensory and Temporal Relatedness—0
Modeling Polyp Activity of Paragorgia arborea Using Supervised Learning—0
Liquid Structural State-Space ModelsCode2
Myopia prediction for adolescents via time-aware deep learning—0
Neural State-Space Modeling with Latent Causal-Effect DisentanglementCode0
A Deep Learning Approach to Analyzing Continuous-Time SystemsCode1
High-Resolution Satellite Imagery for Modeling the Impact of Aridification on Crop Production—0
Asset Pricing and Deep Learning—0
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions—0
Physics-Informed Graph Neural Network for Spatial-temporal Production Forecasting—0
Multivariate Wasserstein Functional Connectivity for Autism Screening—0
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions—0
A Robust and Explainable Data-Driven Anomaly Detection Approach For Power Electronics—0
Deep learning based sferics recognition for AMT data processing in the dead band—0
Optimal Stopping with Gaussian Processes—0
STING: Self-attention based Time-series Imputation Networks using GAN—0
StyleTime: Style Transfer for Synthetic Time Series Generation—0
Robust Forecasting for Robotic Control: A Game-Theoretic Approach—0
Multiscale Comparison of Nonparametric Trend Curves—0
Combined Unbalanced Distribution System State and Line Impedance Matrix Estimation—0
OLIVES Dataset: Ophthalmic Labels for Investigating Visual Eye SemanticsCode1
Anomaly Detection on Financial Time Series by Principal Component Analysis and Neural NetworksCode0
An Image Processing approach to identify solar plages observed at 393.37 nm by the Kodaikanal Solar ObservatoryCode0
Contrastive Learning for Time Series on Dynamic Graphs—0
Review of Time Series Forecasting Methods and Their Applications to Particle Accelerators—0
DeepVARwT: Deep Learning for a VAR Model with TrendCode1
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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