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 251–260 of 477 papers

TitleStatusHype
Fourier-RNNs for Modelling Noisy Physics Data—0
Deep learning for ψ-weakly dependent processes—0
Effect of temporal resolution on the reproduction of chaotic dynamics via reservoir computing—0
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing—0
Efficient Online Learning with Memory via Frank-Wolfe Optimization: Algorithms with Bounded Dynamic Regret and Applications to Control—0
Construction of a Surrogate Model: Multivariate Time Series Prediction with a Hybrid Model—0
Data-driven Real-time Short-term Prediction of Air Quality: Comparison of ES, ARIMA, and LSTM—0
HigeNet: A Highly Efficient Modeling for Long Sequence Time Series Prediction in AIOpsCode0
Reservoir Computing via Quantum Recurrent Neural Networks—0
Layer-wise Relevance Propagation for Echo State Networks applied to Earth System Variability—0
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Benchmark Results

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