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 361–370 of 477 papers

TitleStatusHype
Non-Volatile Memory Array Based Quantization- and Noise-Resilient LSTM Neural Networks—0
Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost—0
On a novel training algorithm for sequence-to-sequence predictive recurrent networks—0
Online Learning with Predictable Sequences—0
Online Multi-horizon Transaction Metric Estimation with Multi-modal Learning in Payment Networks—0
Online Training of an Opto-Electronic Reservoir Computer Applied to Real-Time Channel Equalisation—0
On Multivariate Singular Spectrum Analysis and its Variants—0
On the Benefits of Biophysical Synapses—0
On the suitability of generalized regression neural networks for GNSS position time series prediction for geodetic applications in geodesy and geophysics—0
Optimal training of finitely-sampled quantum reservoir computers for forecasting of chaotic dynamics—0
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Benchmark Results

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