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 61–70 of 477 papers

TitleStatusHype
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic ForecastingCode1
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series PredictionCode1
How Does It Function? Characterizing Long-term Trends in Production Serverless WorkloadsCode1
IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series PredictionCode1
AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the FlyCode1
Deep and Confident Prediction for Time Series at UberCode1
Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series ForecastingCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
Bayesian Neural Architecture Search using A Training-Free Performance MetricCode1
Leveraging 2D Information for Long-term Time Series Forecasting with Vanilla TransformersCode1
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Benchmark Results

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