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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 5201–5250 of 6748 papers

TitleStatusHype
On Policy Evaluation with Aggregate Time-Series Shocks—0
On Principal Curve-Based Classifiers and Similarity-Based Selective Sampling in Time-Series—0
On Recursive Edit Distance Kernels with Application to Time Series Classification—0
On Robust Inference in Time Series Regression—0
On Selecting Stable Predictors in Time Series Models—0
On Sparse High-Dimensional Graphical Model Learning For Dependent Time Series—0
On stabilizing the variance of dynamic functional brain connectivity time series—0
On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning—0
On the balance between the training time and interpretability of neural ODE for time series modelling—0
On the Benefits of Biophysical Synapses—0
On the benefits of maximum likelihood estimation for Regression and Forecasting—0
On The Complexity of Sparse Label Propagation—0
On the Duality between Network Flows and Network Lasso—0
On the Initialization of Long Short-Term Memory Networks—0
On the interplay between multiscaling and stocks dependence—0
On the Linearity of Semantic Change: Investigating Meaning Variation via Dynamic Graph Models—0
On the LRD of the Aggregated Traffic Flows in High-Speed Computer Networks—0
On the LRD of the Aggregated Traffic Flows in High-Speed Computer Networks—0
On the Opportunities of Green Computing: A Survey—0
On the Parameterization and Initialization of Diagonal State Space Models—0
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification—0
On the Regularization of Learnable Embeddings for Time Series Processing—0
On the semantics of big Earth observation data for land classification—0
On the short term stability of financial ARCH price processes—0
On the statistics of scaling exponents and the Multiscaling Value at Risk—0
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection—0
On the suitability of generalized regression neural networks for GNSS position time series prediction for geodetic applications in geodesy and geophysics—0
On the Susceptibility and Robustness of Time Series Models through Adversarial Attack and Defense—0
On the Theory and Practice of Privacy-Preserving Bayesian Data Analysis—0
On the Time Series Length for an Accurate Fractal Analysis in Network Systems—0
A tale of two toolkits, report the third: on the usage and performance of HIVE-COTE v1.0—0
On the Usage of Generative Models for Network Anomaly Detection in Multivariate Time-Series—0
On the Use of Dimension Reduction or Signal Separation Methods for Nitrogen River Pollution Source Identification—0
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
On the use of Singular Spectrum Analysis—0
On the Use of Time Series Kernel and Dimensionality Reduction to Identify the Acquisition of Antimicrobial Multidrug Resistance in the Intensive Care Unit—0
On the variability of functional connectivity and network measures in source-reconstructed EEG time-series—0
Operator Autoencoders: Learning Physical Operations on Encoded Molecular Graphs—0
OPP-Miner: Order-preserving sequential pattern mining—0
Optimal Attack against Autoregressive Models by Manipulating the Environment—0
Optimal change point detection in Gaussian processes—0
Optimal Combination Forecasts on Retail Multi-Dimensional Sales Data—0
Optimal Copula Transport for Clustering Multivariate Time Series—0
Optimal Event Monitoring through Internet Mashup over Multivariate Time Series—0
Optimal Latent Space Forecasting for Large Collections of Short Time Series Using Temporal Matrix Factorization—0
Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes—0
Optimally fuzzy temporal memory—0
Optimal model-free prediction from multivariate time series—0
Optimal Policies for Observing Time Series and Related Restless Bandit Problems—0
Optimal Prediction Intervals for Macroeconomic Time Series Using Chaos and NSGA II—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