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 801–850 of 6748 papers

TitleStatusHype
Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic ForecastingCode1
k-Nearest Neighbour Classifiers: 2nd Edition (with Python examples)Code1
Disentangled Sticky Hierarchical Dirichlet Process Hidden Markov ModelCode1
From Fourier to Koopman: Spectral Methods for Long-term Time Series PredictionCode1
A Spatio-Temporal Spot-Forecasting Framework for Urban Traffic PredictionCode1
FastDTW is approximate and Generally Slower than the Algorithm it ApproximatesCode1
Generative ODE Modeling with Known UnknownsCode1
Spatio-Temporal Graph Convolution for Resting-State fMRI AnalysisCode1
Construe: a software solution for the explanation-based interpretation of time seriesCode1
Human Activity Recognition from Wearable Sensor Data Using Self-AttentionCode1
An Evaluation of Change Point Detection AlgorithmsCode1
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure EvolutionCode1
FusionLane: Multi-Sensor Fusion for Lane Marking Semantic Segmentation Using Deep Neural NetworksCode1
Adversarial Attacks on Probabilistic Autoregressive Forecasting ModelsCode1
On the performance of deep learning models for time series classification in streamingCode1
Forecasting Sequential Data using Consistent Koopman AutoencodersCode1
Dimensionality reduction to maximize prediction generalization capabilityCode1
A Time-dependent SIR model for COVID-19 with Undetectable Infected PersonsCode1
Omni-Scale CNNs: a simple and effective kernel size configuration for time series classificationCode1
Modeling Continuous Stochastic Processes with Dynamic Normalizing FlowsCode1
Causal structure learning from time series: Large regression coefficients may predict causal links better in practice than small p-valuesCode1
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity DetectionCode1
Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural NetworkCode1
Forecasting Foreign Exchange Rate: A Multivariate Comparative Analysis between Traditional Econometric, Contemporary Machine Learning & Deep Learning TechniquesCode1
Deep reconstruction of strange attractors from time seriesCode1
ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series ForecastingCode1
Selecting time-series hyperparameters with the artificial jackknifeCode1
A Physiology-Driven Computational Model for Post-Cardiac Arrest Outcome PredictionCode1
Improving S&P stock prediction with time series stock similarityCode1
Meta-learning framework with applications to zero-shot time-series forecastingCode1
DYNOTEARS: Structure Learning from Time-Series DataCode1
Variable-lag Granger Causality and Transfer Entropy for Time Series AnalysisCode1
Bayesian Neural Architecture Search using A Training-Free Performance MetricCode1
Deep Transformer Models for Time Series Forecasting: The Influenza Prevalence CaseCode1
Generalization of Change-Point Detection in Time Series Data Based on Direct Density Ratio EstimationCode1
Mind the gap: an experimental evaluation of imputation of missing values techniques in time seriesCode1
Explainable Deep Convolutional Candlestick LearnerCode1
Discovering Nonlinear Relations with Minimum Predictive Information RegularizationCode1
Root Cause Detection Among Anomalous Time Series Using Temporal State AlignmentCode1
Source Model Selection for Deep Learning in the Time Series DomainCode1
Variable-lag Granger Causality for Time Series AnalysisCode1
High-Dimensional Granger Causality Tests with an Application to VIX and NewsCode1
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural NetworksCode1
Temporal Knowledge Graph Embedding Model based on Additive Time Series DecompositionCode1
U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep StagingCode1
Spatio-Temporal Alignments: Optimal transport through space and timeCode1
Shape and Time Distortion Loss for Training Deep Time Series Forecasting ModelsCode1
Synthesis of Realistic ECG using Generative Adversarial NetworksCode1
InceptionTime: Finding AlexNet for Time Series ClassificationCode1
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval PredictorsCode1
Show:102550
← PrevPage 17 of 135Next →
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