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 11–20 of 477 papers

TitleStatusHype
Liquid Time-constant NetworksCode2
Deep Learning for Time Series Forecasting: Tutorial and Literature SurveyCode2
Bayesian Temporal Factorization for Multidimensional Time Series PredictionCode2
IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series PredictionCode1
CMoS: Rethinking Time Series Prediction Through the Lens of Chunk-wise Spatial CorrelationsCode1
Error-quantified Conformal Inference for Time SeriesCode1
SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series ForecastingCode1
PowerMamba: A Deep State Space Model and Comprehensive Benchmark for Time Series Prediction in Electric Power SystemsCode1
Recursive Gaussian Process State Space ModelCode1
An Evaluation of Deep Learning Models for Stock Market Trend PredictionCode1
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Benchmark Results

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