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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 3051–3100 of 6748 papers

TitleStatusHype
Distributed Online Learning with Multiple Kernels—0
Deep Video Prediction for Time Series Forecasting—0
AutoAI-TS: AutoAI for Time Series Forecasting—0
Partially Hidden Markov Chain Linear Autoregressive model: inference and forecastingCode0
Similarity measure for sparse time course data based on Gaussian processesCode0
Estimation of Continuous Blood Pressure from PPG via a Federated Learning ApproachCode1
"Train one, Classify one, Teach one" -- Cross-surgery transfer learning for surgical step recognition—0
Dynamic Social Media Monitoring for Fast-Evolving Online Discussions—0
Non-stationary GARCH modelling for fitting higher order moments of financial series within moving time windows—0
Optimal Prediction Intervals for Macroeconomic Time Series Using Chaos and NSGA II—0
When is Early Classification of Time Series Meaningful?—0
The SpaceNet Multi-Temporal Urban Development Challenge—0
Model-Attentive Ensemble Learning for Sequence Modeling—0
Bridging factor and sparse models—0
Phase Space Reconstruction Network for Lane Intrusion Action Recognition—0
Neural Pharmacodynamic State Space ModelingCode0
Delhi air quality prediction using LSTM deep learning models with a focus on COVID-19 lockdownCode1
nTreeClus: a Tree-based Sequence Encoder for Clustering Categorical SeriesCode0
Elastic Similarity and Distance Measures for Multivariate Time SeriesCode0
Approximate Bayes factors for unit root testing—0
Joint Characterization of Multiscale Information in High Dimensional Data—0
Composable Generative Models—0
Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks—0
Performance Dependency of LSTM and NAR Beamformers With Respect to Sensor Array Properties in V2I Scenario—0
Analysis of EEG data using complex geometric structurization—0
Identification of Phase-Locked Loop System From Its Experimental Time Series—0
Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters—0
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification—0
Crop mapping from image time series: deep learning with multi-scale label hierarchiesCode1
Testing for Nonlinear Cointegration under Heteroskedasticity—0
POLA: Online Time Series Prediction by Adaptive Learning Rates—0
Robust Domain-Free Domain Generalization with Class-aware Alignment—0
Pattern Sampling for Shapelet-based Time Series Classification—0
Robust Factorization of Real-world Tensor Streams with Patterns, Missing Values, and OutliersCode1
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals—0
Adaptive Weighting Scheme for Automatic Time-Series Data Augmentation—0
Classification of multivariate weakly-labelled time-series with attentionCode0
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural NetworksCode1
Dynamic Virtual Graph Significance Networks for Predicting InfluenzaCode0
A Complex Systems Approach To Feature Extraction for Chaotic Behavior RecognitionCode0
Controlling False Discovery Rates under Cross-Sectional Correlations—0
An Operator Theoretic Approach for Analyzing Sequence Neural NetworksCode0
Geometric feature performance under downsampling for EEG classification tasks—0
Network of Tensor Time SeriesCode1
Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time SeriesCode1
Tight lower bounds for Dynamic Time WarpingCode0
On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning—0
Domain Adaptation for Time Series Forecasting via Attention SharingCode1
Clustering Interval-Censored Time-Series for Disease Phenotyping—0
How Far Should We Look Back to Achieve Effective Real-Time Time-Series Anomaly Detection?—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