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 161–170 of 477 papers

TitleStatusHype
AutoCas: Autoregressive Cascade Predictor in Social Networks via Large Language Models—0
Deterministic Reservoir Computing for Chaotic Time Series Prediction—0
Density Matrix Emulation of Quantum Recurrent Neural Networks for Multivariate Time Series Prediction—0
An Alternate View on Optimal Filtering in an RKHS—0
Demystifying the Communication Characteristics for Distributed Transformer Models—0
A Transformer-based Framework For Multi-variate Time Series: A Remaining Useful Life Prediction Use Case—0
An algorithmic framework for the optimization of deep neural networks architectures and hyperparameters—0
Deep Reservoir Networks with Learned Hidden Reservoir Weights using Direct Feedback Alignment—0
Deep Reinforcement Learning for Asset Allocation in US Equities—0
Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systems—0
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Benchmark Results

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