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 64516500 of 6748 papers

TitleStatusHype
Time Series Cluster Kernel for Learning Similarities between Multivariate Time Series with Missing DataCode0
A Multi-Horizon Quantile Recurrent ForecasterCode0
Examining COVID-19 Forecasting using Spatio-Temporal Graph Neural NetworksCode0
Clustering Market Regimes using the Wasserstein DistanceCode0
Automatic Cardiac Disease Assessment on cine-MRI via Time-Series Segmentation and Domain Specific FeaturesCode0
Model Agnostic Time Series Analysis via Matrix EstimationCode0
Semi-supervised Sequence Modeling for Elastic Impedance InversionCode0
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent statesCode0
Clustering Based Feature Learning on Variable StarsCode0
Set Functions for Time SeriesCode0
YASS: Yet Another Spike SorterCode0
Prediction of Landfall Intensity, Location, and Time of a Tropical CycloneCode0
Model Compression for Dynamic Forecast CombinationCode0
Shallow RNN: Accurate Time-series Classification on Resource Constrained DevicesCode0
Class-Specific Explainability for Deep Time Series ClassifiersCode0
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series ForecastCode0
ShapeDBA: Generating Effective Time Series Prototypes using ShapeDTW Barycenter AveragingCode0
Trading via Image ClassificationCode0
shapeDTW: shape Dynamic Time WarpingCode0
Shapelet-Based Counterfactual Explanations for Multivariate Time SeriesCode0
Task-oriented Time Series Imputation Evaluation via Generalized RepresentersCode0
Predictive Auto-scaling with OpenStack MonascaCode0
Structured Recognition for Generative Models with Explaining AwayCode0
A persistent homology approach to heart rate variability analysis with an application to sleep-wake classificationCode0
Time Series Data Cleaning: From Anomaly Detection to Anomaly RepairingCode0
Taylor's law for Human Linguistic SequencesCode0
Evolving-Graph Gaussian ProcessesCode0
Deep Learning for Human Locomotion Analysis in Lower-Limb Exoskeletons: A Comparative StudyCode0
ShortFuse: Biomedical Time Series Representations in the Presence of Structured InformationCode0
Automatic Anomaly Detection in the Cloud Via Statistical LearningCode0
Deep learning for gravitational-wave data analysis: A resampling white-box approachCode0
Modeling EEG data distribution with a Wasserstein Generative Adversarial Network to predict RSVP EventsCode0
Modeling emotion in complex stories: the Stanford Emotional Narratives DatasetCode0
TC-DTW: Accelerating Multivariate Dynamic Time Warping Through Triangle Inequality and Point ClusteringCode0
T-CGAN: Conditional Generative Adversarial Network for Data Augmentation in Noisy Time Series with Irregular SamplingCode0
Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costsCode0
Modeling Irregularly Sampled Clinical Time SeriesCode0
Event Detection via Probability Density Function RegressionCode0
Short-term daily precipitation forecasting with seasonally-integrated autoencoderCode0
Deep learning for clustering of multivariate clinical patient trajectories with missing valuesCode0
EVARS-GPR: EVent-triggered Augmented Refitting of Gaussian Process Regression for Seasonal DataCode0
Using Clinical Drug Representations for Improving Mortality and Length of Stay PredictionsCode0
Deep learning-based electroencephalography analysis: a systematic reviewCode0
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for BrazilCode0
CNTLS: A Benchmark Dataset for Abstractive or Extractive Chinese Timeline SummarizationCode0
Your time series is worth a binary image: machine vision assisted deep framework for time series forecastingCode0
Automated Deep Abstractions for Stochastic Chemical Reaction NetworksCode0
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden ConfoundersCode0
Using Clinical Notes with Time Series Data for ICU ManagementCode0
TEASER: Early and Accurate Time Series ClassificationCode0
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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