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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1751–1775 of 6748 papers

TitleStatusHype
Spatiotemporal Cardiac Statistical Shape Modeling: A Data-Driven Approach—0
Features Fusion Framework for Multimodal Irregular Time-series Events—0
Recursive Gaussian Process over graphs for Integrating Multi-timescale Measurements in Low-Observable Distribution Systems—0
Learning Differential Operators for Interpretable Time Series Modeling—0
An Interpretable and Efficient Infinite-Order Vector Autoregressive Model for High-Dimensional Time Series—0
An Explainer for Temporal Graph Neural Networks—0
Universal Fourier Attack for Time Series—0
In Situ 3D Spatiotemporal Measurement of Soluble Biomarkers in Organoid Culture—0
Estimation of Correlation Matrices from Limited time series Data using Machine Learning—0
Recurrent LSTM-based UAV Trajectory Prediction with ADS-B Information—0
Progressive Fusion for Multimodal Integration—0
Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting—0
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution—0
Learning Multiscale Non-stationary Causal Structures—0
Long-term hail risk assessment with deep neural networks—0
Denoising Architecture for Unsupervised Anomaly Detection in Time-SeriesCode0
Large-step neural network for learning the symplectic evolution from partitioned data—0
Persistence Initialization: A novel adaptation of the Transformer architecture for Time Series Forecasting—0
Modeling Volatility and Dependence of European Carbon and Energy Prices—0
High-frequency financial market simulation and flash crash scenarios analysis: an agent-based modelling approach—0
Understanding intra-day price formation process by agent-based financial market simulation: calibrating the extended chiarella model—0
Large-scale unsupervised spatio-temporal semantic analysis of vast regions from satellite images sequences—0
Learning Informative Health Indicators Through Unsupervised Contrastive Learning—0
A restricted eigenvalue condition for unit-root non-stationary data—0
Riesz-Quincunx-UNet Variational Auto-Encoder for Satellite Image DenoisingCode0
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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