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 241–250 of 477 papers

TitleStatusHype
Kernel Least Mean Square with Adaptive Kernel Size—0
Landslide Surface Displacement Prediction Based on VSXC-LSTM Algorithm—0
Time Series Forecasting with Stacked Long Short-Term Memory Networks—0
Large Language Model (LLM) for Telecommunications: A Comprehensive Survey on Principles, Key Techniques, and Opportunities—0
Large-Scale Spectrum Occupancy Learning via Tensor Decomposition and LSTM Networks—0
A Transformer-based Framework For Multi-variate Time Series: A Remaining Useful Life Prediction Use Case—0
Learning Hamiltonian Dynamics with Bayesian Data Assimilation—0
Learning Novel Transformer Architecture for Time-series Forecasting—0
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes—0
Learning to Program Variational Quantum Circuits with Fast Weights—0
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Benchmark Results

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