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 71–80 of 477 papers

TitleStatusHype
Dimensionality reduction to maximize prediction generalization capabilityCode1
Bayesian Neural Architecture Search using A Training-Free Performance MetricCode1
Legendre Memory Units: Continuous-Time Representation in Recurrent Neural NetworksCode1
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic ForecastingCode1
Deep and Confident Prediction for Time Series at UberCode1
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic ForecastingCode1
Recurrent Neural Networks for Multivariate Time Series with Missing ValuesCode1
Wavelet-Enhanced Neural ODE and Graph Attention for Interpretable Energy Forecasting—0
Predicting Graph Structure via Adapted Flux Balance AnalysisCode0
SEED: A Structural Encoder for Embedding-Driven Decoding in Time Series Prediction with LLMs—0
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Benchmark Results

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