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 291–300 of 477 papers

TitleStatusHype
Spatiotemporal information conversion machine for time-series predictionCode1
On a novel training algorithm for sequence-to-sequence predictive recurrent networks—0
Closed-form Continuous-time Neural ModelsCode2
ScoreGrad: Multivariate Probabilistic Time Series Forecasting with Continuous Energy-based Generative ModelsCode1
Distributed Learning and its Application for Time-Series Prediction—0
Prediction of the Position of External Markers Using a Recurrent Neural Network Trained With Unbiased Online Recurrent Optimization for Safe Lung Cancer RadiotherapyCode1
CVaR-based Flight Energy Risk Assessment for Multirotor UAVs using a Deep Energy ModelCode1
Generative Network-Based Reduced-Order Model for Prediction, Data Assimilation and Uncertainty QuantificationCode1
Photonic neural field on a silicon chip: large-scale, high-speed neuro-inspired computing and sensing—0
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
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Benchmark Results

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