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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–700 of 6748 papers

TitleStatusHype
catch22: CAnonical Time-series CHaracteristicsCode1
Forecasting Sequential Data using Consistent Koopman AutoencodersCode1
Forecasting with sktime: Designing sktime's New Forecasting API and Applying It to Replicate and Extend the M4 StudyCode1
Forecasting with time series imagingCode1
From point forecasts to multivariate probabilistic forecasts: The Schaake shuffle for day-ahead electricity price forecastingCode1
From Time Series to Networks in R with the ts2net PackageCode1
Fully Spiking Variational AutoencoderCode1
FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural NetworksCode1
Can LLMs Understand Time Series Anomalies?Code1
Generalised Interpretable Shapelets for Irregular Time SeriesCode1
Generalized Classification of Satellite Image Time Series with Thermal Positional EncodingCode1
Generative adversarial networks in time series: A survey and taxonomyCode1
A general framework for multi-step ahead adaptive conformal heteroscedastic time series forecastingCode1
Can Multimodal LLMs Perform Time Series Anomaly Detection?Code1
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
Graph-Guided Network for Irregularly Sampled Multivariate Time SeriesCode1
Arbitrage-free neural-SDE market modelsCode1
Generating multivariate time series with COmmon Source CoordInated GAN (COSCI-GAN)Code1
Calibrated One-class Classification for Unsupervised Time Series Anomaly DetectionCode1
HARNet: A Convolutional Neural Network for Realized Volatility ForecastingCode1
CALDA: Improving Multi-Source Time Series Domain Adaptation with Contrastive Adversarial LearningCode1
Highly comparative time-series analysis: The empirical structure of time series and their methodsCode1
HiPPO: Recurrent Memory with Optimal Polynomial ProjectionsCode1
A Reinforcement Learning Based Encoder-Decoder Framework for Learning Stock Trading RulesCode1
Calibration of Google Trends Time SeriesCode1
How to find a unicorn: a novel model-free, unsupervised anomaly detection method for time seriesCode1
Human Activity Recognition from Wearable Sensor Data Using Self-AttentionCode1
Building an Automated and Self-Aware Anomaly Detection SystemCode1
ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical ImagesCode1
Imaging Time-Series to Improve Classification and ImputationCode1
Improving Clinical Outcome Predictions Using Convolution over Medical Entities with Multimodal LearningCode1
A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series DataCode1
Improving Position Encoding of Transformers for Multivariate Time Series ClassificationCode1
A Review of Graph Neural Networks and Their Applications in Power SystemsCode1
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time WarpingCode1
Inductive Graph Neural Networks for Spatiotemporal KrigingCode1
Active multi-fidelity Bayesian online changepoint detectionCode1
A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality ModelingCode1
Integrated multimodal artificial intelligence framework for healthcare applicationsCode1
Integrating LSTMs and GNNs for COVID-19 ForecastingCode1
Interpretable Multivariate Time Series Forecasting with Temporal Attention Convolutional Neural NetworksCode1
Interpretable Time Series Classification using All-Subsequence Learning and Symbolic Representations in Time and Frequency DomainsCode1
Interpretable Time-series Classification on Few-shot SamplesCode1
Interpreting Machine Learning Models for Room Temperature Prediction in Non-domestic BuildingsCode1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval PredictorsCode1
CAMul: Calibrated and Accurate Multi-view Time-Series ForecastingCode1
Are we certain it's anomalous?Code1
Jumping VaR: Order Statistics Volatility Estimator for Jumps Classification and Market Risk ModelingCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural NetworksCode1
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All datasetsPhysioNet Challenge 2012Speech CommandsVentilator Pressure Prediction

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