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 2226–2250 of 6748 papers

TitleStatusHype
Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module—0
Autoregressive-Model-Based Methods for Online Time Series Prediction with Missing Values: an Experimental Evaluation—0
A new approach to the modeling of financial volumes—0
Deep Reinforcement Learning for Asset Allocation in US Equities—0
Deep Reinforcement Learning Assisted Federated Learning Algorithm for Data Management of IIoT—0
Autoregressive GNN-ODE GRU Model for Network Dynamics—0
Deep Recurrent Neural Networks for Time Series Prediction—0
Deep Recurrent Neural Networks for mapping winter vegetation quality coverage via multi-temporal SAR Sentinel-1—0
A new approach for physiological time series—0
Deep Recurrent Modelling of Granger Causality with Latent Confounding—0
Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters—0
Deep Recurrent Convolutional Networks for Video-based Person Re-identification: An End-to-End Approach—0
An Evolving Cascade System Based on A Set Of Neo Fuzzy Nodes—0
Adversarially learned anomaly detection for time series data—0
A Comprehensive Study on Various Statistical Techniques for Prediction of Movie Success—0
ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series—0
Recurrent Neural Network-based Model for Accelerated Trajectory Analysis in AIMD Simulations—0
Real-Time Privacy-Preserving Data Release for Smart Meters—0
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting—0
DeepRain: ConvLSTM Network for Precipitation Prediction using Multichannel Radar Data—0
Deep Q-network using reservoir computing with multi-layered readout—0
An Evaluation of Low Overhead Time Series Preprocessing Techniques for Downstream Machine Learning—0
Deep Probabilistic Time Series Forecasting using Augmented Recurrent Input for Dynamic Systems—0
Deep Probabilistic Koopman: Long-term time-series forecasting under periodic uncertainties—0
Deep Poisson gamma dynamical systems—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