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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 3901–3950 of 6748 papers

TitleStatusHype
Short-Term Memory Convolutions—0
Experimental Investigation of Variational Mode Decomposition and Deep Learning for Short-Term Multi-horizon Residential Electric Load Forecasting—0
Short-term Prediction of Household Electricity Consumption Using Customized LSTM and GRU Models—0
Short-term prediction of stream turbidity using surrogate data and a meta-model approach—0
Short-term prediction of Time Series based on bounding techniques—0
Short-term Road Traffic Prediction based on Deep Cluster at Large-scale Networks—0
Short-term solar irradiance and irradiation forecasts via different time series techniques: A preliminary study—0
Short-Term Stock Price-Trend Prediction Using Meta-Learning—0
Short-term time series prediction using Hilbert space embeddings of autoregressive processes—0
Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework—0
Short-Term Traffic Forecasting Using High-Resolution Traffic Data—0
Short-term Wind Speed Forecasting based on LSSVM Optimized by Elitist QPSO—0
Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models—0
Short- to Mid-term Day-Ahead Electricity Price Forecasting Using Futures—0
Should we Reload Time Series Classification Performance Evaluation ? (a position paper)—0
Show Me Your Account: Detecting MMORPG Game Bot Leveraging Financial Analysis with LSTM—0
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data—0
Signal automata and hidden Markov models—0
Signal Classification using Smooth Coefficients of Multiple wavelets—0
Signal Fluctuation Sensitivity: an improved metric for optimizing detection of resting-state fMRI networks—0
Signal Processing on Graphs: Causal Modeling of Unstructured Data—0
Signal processing on simplicial complexes—0
Signal Restoration and Channel Estimation for Channel Sounding with SDRs—0
Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognition—0
Signatures Meet Dynamic Programming: Generalizing Bellman Equations for Trajectory Following—0
Signatures of brain criticality unveiled by maximum entropy analysis across cortical states—0
Signs in time: Encoding human motion as a temporal image—0
Sig-SDEs model for quantitative finance—0
Silicon Photonic Microring Based Chip-Scale Accelerator for Delayed Feedback Reservoir Computing—0
SILVar: Single Index Latent Variable Models—0
Similarity Grouping-Guided Neural Network Modeling for Maritime Time Series Prediction—0
Similarity Learning for Time Series Classification—0
Similarity measure for Public Persons—0
Similarity Preserving Representation Learning for Time Series Clustering—0
Simple Models and Biased Forecasts—0
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition—0
Simplicial persistence of financial markets: filtering, generative processes and portfolio risk—0
Simulated Data Experiments for Time Series Classification Part 1: Accuracy Comparison with Default Settings—0
Simulating extrapolated dynamics with parameterization networks—0
Simulating financial time series using attention—0
Simulating Network Paths with Recurrent Buffering Units—0
Simulating User-Level Twitter Activity with XGBoost and Probabilistic Hybrid Models—0
Simulating Using Deep Learning The World Trade Forecasting of Export-Import Exchange Rate Convergence Factor During COVID-19—0
Simultaneous Implementation Features Extraction and Recognition Using C3D Network for WiFi-based Human Activity Recognition—0
Simultaneous Multivariate Forecast of Space Weather Indices using Deep Neural Network Ensembles—0
Sinkhorn-Flow: Predicting Probability Mass Flow in Dynamical Systems Using Optimal Transport—0
Size-Consistent Statistics for Anomaly Detection in Dynamic Networks—0
Skeletonnet: Mining deep part features for 3-d action recognition—0
Gaussian Processes with Skewed Laplace Spectral Mixture Kernels for Long-term Forecasting—0
Skill Analysis with Time Series Image Data—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