SOTAVerified

Time Series Prediction

The goal of Time Series Prediction is to infer the future values of a time series from the past.

Source: Orthogonal Echo State Networks and stochastic evaluations of likelihoods

Papers

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Showing 301–325 of 477 papers

TitleStatusHype
Finite volume method network for acceleration of unsteady computational fluid dynamics: non-reacting and reacting flows—0
Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases—0
A windowed correlation based feature selection method to improve time series prediction of dengue fever cases—0
DeepSITH: Efficient Learning via Decomposition of What and When Across Time ScalesCode1
Evaluation of deep learning models for multi-step ahead time series predictionCode1
Machine Learning Prediction of Time-Varying Rayleigh Channels—0
PyRCN: A Toolbox for Exploration and Application of Reservoir Computing NetworksCode1
Distributed Online Learning with Multiple Kernels—0
POLA: Online Time Series Prediction by Adaptive Learning Rates—0
Dynamic Virtual Graph Significance Networks for Predicting InfluenzaCode0
A Review of Graph Neural Networks and Their Applications in Power SystemsCode1
Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data—0
A General Framework for Hypercomplex-valued Extreme Learning Machines—0
Unveiling the role of plasticity rules in reservoir computing—0
Graph Edit NetworksCode0
Modified Auto Regressive Technique for Univariate Time Series Prediction of Solar Irradiance—0
Learn to Predict Vertical Track Irregularity with Extremely Imbalanced Data—0
Recursive Tree Grammar AutoencodersCode0
Explainable Tensorized Neural Ordinary Differential Equations forArbitrary-step Time Series PredictionCode0
Backpropagation-Free Learning Method for Correlated Fuzzy Neural Networks—0
Continuous Ant-Based Neural Topology Search—0
Distributed Online Learning with Multiple Kernels—0
ATCN: Resource-Efficient Processing of Time Series on EdgeCode0
Time Series Forecasting with Stacked Long Short-Term Memory Networks—0
Deep Reservoir Networks with Learned Hidden Reservoir Weights using Direct Feedback Alignment—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CMU-DEMAverage mean absolute error9.06—Unverified
#ModelMetricClaimedVerifiedStatus
1LSTMRMSE0—Unverified