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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 2051–2100 of 6748 papers

TitleStatusHype
Deep Decomposition for Stochastic Normal-Abnormal Transport—0
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series ClassificationCode0
Self-supervised Autoregressive Domain Adaptation for Time Series DataCode1
NeuralProphet: Explainable Forecasting at ScaleCode2
TsFeX: Contact Tracing Model using Time Series Feature Extraction and Gradient Boosting—0
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes—0
Improving Deep Learning Interpretability by Saliency Guided TrainingCode1
Enhancing Identification of Structure Function of Academic Articles Using Contextual InformationCode0
Learning Wildfire Model from Incomplete State Observations—0
Learning Physical Concepts in Cyber-Physical Systems: A Case StudyCode0
Factor-augmented tree ensemblesCode0
Automated Antenna Testing Using Encoder-Decoder-based Anomaly Detection—0
Achieving an Accurate Random Process Model for PV Power using Cheap Data: Leveraging the SDE and Public Weather Reports—0
Correlation Based Feature Subset Selection for Multivariate Time-Series Data—0
SARS-CoV-2 Dissemination using a Network of the United States Counties—0
A Variational Inference Approach to Inverse Problems with Gamma Hyperpriors—0
Amercing: An Intuitive, Elegant and Effective Constraint for Dynamic Time WarpingCode1
Wavelet‐attention‐based traffic prediction for smart cities—0
Expert Aggregation for Financial Forecasting—0
Learning dynamical systems from data: A simple cross-validation perspective, part III: Irregularly-Sampled Time SeriesCode0
A Deep Learning Approach for Macroscopic Energy Consumption Prediction with Microscopic Quality for Electric Vehicles—0
Neural network stochastic differential equation models with applications to financial data forecastingCode1
Animal Behavior Classification via Accelerometry Data and Recurrent Neural Networks—0
Animal behavior classification via deep learning on embedded systems—0
tsflex: flexible time series processing & feature extractionCode1
Causal Analysis and Prediction of Human Mobility in the U.S. during the COVID-19 Pandemic—0
Interpreting Machine Learning Models for Room Temperature Prediction in Non-domestic BuildingsCode1
Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles -- Extended Version—0
Light-weight Gesture Sensing Using FMCW Radar Time Series Data—0
4D iterative reconstruction of brain fMRI in the moving fetus—0
Modeling Irregular Time Series with Continuous Recurrent UnitsCode1
Time Series Prediction about Air Quality using LSTM-Based Models: A Systematic Mapping—0
Learning Non-Stationary Time-Series with Dynamic Pattern Extractions—0
Vehicular Visible Light Communications Noise Analysis and Autoencoder Based Denoising—0
Unsupervised Visual Time-Series Representation Learning and Clustering—0
How News Evolves? Modeling News Text and Coverage using Graphs and Hawkes Process—0
DeepGuard: A Framework for Safeguarding Autonomous Driving Systems from Inconsistent Behavior—0
A transformer-based model for default prediction in mid-cap corporate markets—0
Causal Forecasting:Generalization Bounds for Autoregressive ModelsCode1
GAETS: A Graph Autoencoder Time Series Approach Towards Battery Parameter Estimation—0
Smart Data Representations: Impact on the Accuracy of Deep Neural NetworksCode0
HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU DataCode1
Uncertainty-Aware Multiple Instance Learning from Large-Scale Long Time Series Data—0
Online Advertising Revenue Forecasting: An Interpretable Deep Learning Approach—0
Switching Recurrent Kalman Networks—0
Towards Generating Real-World Time Series DataCode1
Graph neural network-based fault diagnosis: a review—0
Outlier Detection as Instance Selection Method for Feature Selection in Time Series Classification—0
A similarity measurement for time series and its application to the stock market—0
Machine Learning for Genomic Data—0
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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