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 1951–2000 of 6748 papers

TitleStatusHype
Deep Fusion of Lead-lag Graphs: Application to Cryptocurrencies—0
A Review of Mathematical and Computational Methods in Cancer Dynamics—0
Towards Similarity-Aware Time-Series ClassificationCode1
Elastic Product Quantization for Time SeriesCode0
Graph Neural Networks for Multivariate Time Series Regression with Application to Seismic DataCode1
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection—0
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics—0
Deep Learning and Linear Programming for Automated Ensemble Forecasting and InterpretationCode0
The Interpretability of LSTM Models for Predicting Oil Company Stocks: Impact of Correlated Features—0
Financial time series forecasting with multi-modality graph neural networkCode1
High-dimensional Bayesian Optimization Algorithm with Recurrent Neural Network for Disease Control Models in Time Series—0
Role of Data Augmentation Strategies in Knowledge Distillation for Wearable Sensor DataCode1
Evolutionary correlation, regime switching, spectral dynamics and optimal trading strategies for cryptocurrencies and equities—0
Random cohort effects and age groups dependency structure for mortality modelling and forecasting: Mixed-effects time-series model approach—0
Modelling matrix time series via a tensor CP-decomposition—0
An Efficient Federated Distillation Learning System for Multi-task Time Series Classification—0
ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer—0
An Analysis of an Alternative Pythagorean Expected Win Percentage Model: Applications Using Major League Baseball Team Quality Simulations—0
AutoFITS: Automatic Feature Engineering for Irregular Time SeriesCode0
Monte Carlo EM for Deep Time Series Anomaly DetectionCode0
Cognitive Computing to Optimize IT Services—0
Time-Incremental Learning from Data Using Temporal Logics—0
MOEF: Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate PredictionCode0
Time Series Data Mining Algorithms Towards Scalable and Real-Time Behavior Monitoring—0
Toeplitz Least Squares Problems, Fast Algorithms and Big Data—0
Error-bounded Approximate Time Series Joins Using Compact Dictionary Representations of Time Series—0
Stationarity analysis of the stock market data and its application to mechanical trading—0
A Multi-View Framework for BGP Anomaly Detection via Graph Attention Network—0
Dynamic Combination of Heterogeneous Models for Hierarchical Time Series—0
Neural Echo State Network using oscillations of gas bubbles in water—0
Collaborative adversary nodes learning on the logs of IoT devices in an IoT network—0
AutoCTS: Automated Correlated Time Series Forecasting -- Extended Version—0
PyChEst: a Python package for the consistent retrospective estimation of distributional changes in piece-wise stationary time series—0
Predicting Patient Readmission Risk from Medical Text via Knowledge Graph Enhanced Multiview Graph Convolution—0
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning—0
SSDNet: State Space Decomposition Neural Network for Time Series ForecastingCode0
Multiple Time Series Fusion Based on LSTM An Application to CAP A Phase Classification Using EEGCode0
Discrete signature and its application to financeCode0
A Comparative Study of Detecting Anomalies in Time Series Data Using LSTM and TCN Models—0
A Statistics and Deep Learning Hybrid Method for Multivariate Time Series Forecasting and Mortality ModelingCode1
Trading with the Momentum Transformer: An Intelligent and Interpretable ArchitectureCode1
Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles—0
A CNN based method for Sub-pixel Urban Land Cover Classification using Landsat-5 TM and Resourcesat-1 LISS-IV Imagery—0
A Predictive Online Transient Stability Assessment with Hierarchical Generative Adversarial Networks—0
Real-time Detection of Anomalies in Multivariate Time Series of Astronomical Data—0
Leveraging Image-based Generative Adversarial Networks for Time Series Generation—0
Optimal Latent Space Forecasting for Large Collections of Short Time Series Using Temporal Matrix Factorization—0
Characterization of causal ancestral graphs for time series with latent confounders—0
Compensatory model for quantile estimation and application to VaR—0
Non-iterative Calculation of Quasi-Dynamic Energy Flow in the Heat and Electricity Integrated Energy SystemsCode0
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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