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 5401–5450 of 6748 papers

TitleStatusHype
Predicting Future Sales of Retail Products using Machine Learning—0
Predicting Future Shanghai Stock Market Price using ANN in the Period 21-Sep-2016 to 11-Oct-2016—0
Predicting Individual Responses to Vasoactive Medications in Children with Septic Shock—0
Predicting Intraoperative Hypoxemia with Hybrid Inference Sequence Autoencoder Networks—0
Predicting Learning Status in MOOCs using LSTM—0
Predicting Multidimensional Data via Tensor Learning—0
Predicting Online Item-choice Behavior: A Shape-restricted Regression Perspective—0
Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data—0
Predicting Patient Readmission Risk from Medical Text via Knowledge Graph Enhanced Multiview Graph Convolution—0
Predicting Patient State-of-Health using Sliding Window and Recurrent Classifiers—0
Predicting Mutual Funds' Performance using Deep Learning and Ensemble Techniques—0
Predicting Performance using Approximate State Space Model for Liquid State Machines—0
Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks—0
Predicting Sector Index Movement with Microblogging Public Mood Time Series on Social Issues—0
Predicting Student Performance in an Educational Game Using a Hidden Markov Model—0
Predicting subscriber usage: Analyzing multi-dimensional time-series using Convolutional Neural Networks—0
Predicting Swarm Equatorial Plasma Bubbles via Machine Learning and Shapley Values—0
Predicting Temperature of Major Cities Using Machine Learning and Deep Learning—0
Predicting the 2020 US Presidential Election with Twitter—0
Predicting the Biological Classification of Cell-Cycle Regulated Genes of Saccharomyces cerevisiae using Community Detection Algorithms on Gene Co-expression Networks—0
Predicting the Future is like Completing a Painting!—0
Predicting the Mumble of Wireless Channel with Sequence-to-Sequence Models—0
Predicting the outcome of team movements -- Player time series analysis using fuzzy and deep methods for representation learning—0
Predicting the State of Synchronization of Financial Time Series using Cross Recurrence Plots—0
Predicting the temporal dynamics of turbulent channels through deep learning—0
Predicting Treatment Initiation from Clinical Time Series Data via Graph-Augmented Time-Sensitive Model—0
Predicting Unplanned Readmissions in the Intensive Care Unit: A Multimodality Evaluation—0
Prediction Algorithm for Heat Demand of Science and Technology Topics Based on Time Convolution Network—0
Prediction-Coherent LSTM-based Recurrent Neural Network for Safer Glucose Predictions in Diabetic People—0
On Learning Prediction-Focused Mixtures—0
Prediction of adverse events in Afghanistan: regression analysis of time series data grouped not by geographic dependencies—0
Prediction of Dynamical time Series Using Kernel Based Regression and Smooth Splines—0
Prediction of financial time series using LSTM and data denoising methods—0
Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS—0
Prediction of gene expression time series and structural analysis of gene regulatory networks using recurrent neural networks—0
Prediction of good reaction coordinates and future evolution of MD trajectories using Regularized Sparse Autoencoders: A novel deep learning approach—0
Prediction of hierarchical time series using structured regularization and its application to artificial neural networks—0
Prediction of Hilbertian autoregressive processes : a Recurrent Neural Network approach—0
Prediction of MRI Hardware Failures based on Image Features using Time Series Classification—0
Prediction of Rainfall in Rajasthan, India using Deep and Wide Neural Network—0
Prediction of Sea Surface Temperature using Long Short-Term Memory—0
Prediction of Sentinel-2 multi-band imagery with attention BiLSTM for continuous earth surface monitoring—0
Prediction of short and long-term droughts using artificial neural networks and hydro-meteorological variables—0
Prediction of Traffic Flow via Connected Vehicles—0
Prediction with Spatio-temporal Point Processes with Self Organizing Decision Trees—0
Predictive Analysis of COVID-19 Time-series Data from Johns Hopkins University—0
Predictive-Corrective Networks for Action Detection—0
Predictive Maintenance for General Aviation Using Convolutional Transformers—0
Predictive Process Model Monitoring using Recurrent Neural Networks—0
Equivariant online predictions of non-stationary time series—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