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

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Showing 2401–2450 of 6748 papers

TitleStatusHype
Neural Architecture Searching for Facial Attributes-based Depression Recognition—0
Balanced Graph Structure Learning for Multivariate Time Series ForecastingCode0
Ordinal-Quadruplet: Retrieval of Missing Classes in Ordinal Time Series—0
Multiscale Generative Models: Improving Performance of a Generative Model Using Feedback from Other Dependent Generative ModelsCode0
An Attention-based ConvLSTM Autoencoder with Dynamic Thresholding for Unsupervised Anomaly Detection in Multivariate Time Series—0
Simulating Using Deep Learning The World Trade Forecasting of Export-Import Exchange Rate Convergence Factor During COVID-19—0
Imposing Connectome-Derived Topology on an Echo State Network—0
Fast Transient Stability Prediction Using Grid-informed Temporal and Topological Embedding Deep Neural Network—0
MIDAS: Deep learning human action intention prediction from natural eye movement patterns—0
HiSTGNN: Hierarchical Spatio-temporal Graph Neural Networks for Weather Forecasting—0
Spatiotemporal Analysis Using Riemannian Composition of Diffusion Operators—0
Dynamic Deep Convolutional Candlestick Learner—0
Lead-lag detection and network clustering for multivariate time series with an application to the US equity market—0
Has EU accession boosted patents performance in the EU-13? -- A critical evaluation using causal impact analysis with Bayesian structural time-series models—0
Conditional Generation of Medical Time Series for Extrapolation to Underrepresented PopulationsCode0
Long Short-Term Memory Neural Network for Financial Time Series—0
A sequential Monte Carlo approach to estimate a time varying reproduction number in infectious disease models: the Covid-19 caseCode0
Online Time Series Anomaly Detection with State Space Gaussian Processes—0
Label Dependent Attention Model for Disease Risk Prediction Using Multimodal Electronic Health RecordsCode0
GTrans: Spatiotemporal Autoregressive Transformer with Graph Embeddings for Nowcasting Extreme Events—0
WATCH: Wasserstein Change Point Detection for High-Dimensional Time Series Data—0
Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1D Convolutional Neural Network Approach—0
Improving the quality control of seismic data through active learning—0
Inferential Theory for Granular Instrumental Variables in High Dimensions—0
Predicting waves in fluids with deep neural network—0
Discrete Simulation Optimization for Tuning Machine Learning Method Hyperparameters—0
Forecasting COVID-19 Caseloads Using Unsupervised Embedding Clusters of Social Media Posts—0
Fractional SDE-Net: Generation of Time Series Data with Long-term Memory—0
Enhancement of Healthcare Data Performance Metrics using Neural Network Machine Learning Algorithms—0
Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction—0
A Novel Skeleton-Based Human Activity Discovery Using Particle Swarm Optimization with Gaussian MutationCode0
IDEA: Interpretable Dynamic Ensemble Architecture for Time Series Prediction—0
Imputing Missing Observations with Time Sliced Synthetic Minority Oversampling Technique—0
Recursive Least Squares Policy Control with Echo State Network—0
Privacy Amplification by Subsampling in Time Domain—0
Forecast-based Multi-aspect Framework for Multivariate Time-series Anomaly Detection—0
Time-varying Identification of Guided Wave Propagation under Varying Temperature via Non-Stationary Time Series Models—0
Data augmentation through multivariate scenario forecasting in Data Centers using Generative Adversarial NetworksCode0
Cognitive forces shape the dynamics of word usage across multiple languages—0
Intra-domain and cross-domain transfer learning for time series data -- How transferable are the features?—0
DANNTe: a case study of a turbo-machinery sensor virtualization under domain shift—0
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019—0
Application of Common Spatial Patterns in Gravitational Waves Detection—0
Seizure prediction with long-term iEEG recordings: What can we learn from data nonstationarity?—0
Data-driven approach in a compartmental epidemic model to assess undocumented infectionsCode0
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?—0
A machine learning search for optimal GARCH parameters—0
OPP-Miner: Order-preserving sequential pattern mining—0
Weak Supervision for Affordable Modeling of Electrocardiogram Data—0
Causal Discovery from Sparse Time-Series Data Using Echo State Network—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