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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 5001–5050 of 6748 papers

TitleStatusHype
On Transfer Learning For Chatter Detection in Turning Using Wavelet Packet Transform and Empirical Mode DecompositionCode0
Temporal Graph Convolutional Networks for Automatic Seizure Detection—0
A Novel Trend Symbolic Aggregate Approximation for Time Series—0
Boosting: Why You Can Use the HP FilterCode0
Time-series Insights into the Process of Passing or Failing Online University Courses using Neural-Induced Interpretable Student States—0
Surface Type Classification for Autonomous Robot Indoor Navigation—0
Context-Dependent Semantic Parsing over Temporally Structured DataCode0
Learning Procedural Abstractions and Evaluating Discrete Latent Temporal StructureCode0
The Expressive Power of Gated Recurrent Units as a Continuous Dynamical System—0
Pyramid Recurrent Neural Networks for Multi-Scale Change-Point Detection—0
GEOMETRIC AUGMENTATION FOR ROBUST NEURAL NETWORK CLASSIFIERS—0
A fully automated periodicity detection in time seriesCode0
Neural Causal Discovery with Learnable Input Noise—0
Multi-resolution Networks For Flexible Irregular Time Series Modeling (Multi-FIT)—0
Sequence to sequence deep learning models for solar irradiation forecasting—0
Empirical facts characterizing banking crises: an analysis via binary time series—0
ConvTimeNet: A Pre-trained Deep Convolutional Neural Network for Time Series Classification—0
Curriculum Learning in Deep Neural Networks for Financial Forecasting—0
Rough volatility of Bitcoin—0
Real numbers, data science and chaos: How to fit any dataset with a single parameterCode0
Cough Detection Using Hidden Markov Models—0
Temporal-Clustering Invariance in Irregular Healthcare Time Series—0
Discovering Common Change-Point Patterns in Functional Connectivity Across Subjects—0
Time Series Simulation by Conditional Generative Adversarial Net—0
Predicting Student Performance in an Educational Game Using a Hidden Markov Model—0
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning—0
Community Detection and Growth Potential Prediction from Patent Citation Networks—0
Identifying cross country skiing techniques using power meters in ski polesCode0
Investigating the impact of autocorrelation on time-varying connectivity—0
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series—0
DeepMoD: Deep learning for Model Discovery in noisy dataCode1
Random Fragments Classification of Microbial Marker Clades with Multi-class SVM and N-Best Algorithm—0
Transfer Entropy: where Shannon meets Turing—0
tsmp: An R Package for Time Series with Matrix Profile—0
Explaining Deep Classification of Time-Series Data with Learned PrototypesCode0
Human Motion Prediction via Pattern Completion in Latent Representation Space—0
One-dimensional Deep Image Prior for Time Series Inverse Problems—0
Forecasting Drought Using Multilayer Perceptron Artificial Neural Network Model—0
Forecasting with time series imagingCode1
Forecasting Weakly Correlated Time Series in Tasks of Electronic Commerce—0
DSTP-RNN: a dual-stage two-phase attention-based recurrent neural networks for long-term and multivariate time series prediction—0
Estimation of Cross-Sectional Dependence in Large Panels—0
Automatic Model Building in GEFCom 2017 Qualifying Match—0
Remaining Useful Life Estimation Using Functional Data Analysis—0
Advanced Customer Activity Prediction based on Deep Hierarchic Encoder-Decoders—0
Fractal Time Series Analysis of Social Network Activities—0
Local Polynomial Estimation of Time-Varying Parameters in Nonlinear Models—0
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance MatricesCode0
Discovering patterns of online popularity from time seriesCode0
Generic Variance Bounds on Estimation and Prediction Errors in Time Series Analysis: An Entropy Perspective—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