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 131–140 of 477 papers

TitleStatusHype
Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time SeriesCode0
Recurrent Stochastic Configuration Networks with Incremental Blocks—0
Causal-discovery-based root-cause analysis and its application in time-series prediction error diagnosisCode0
Deep Recurrent Stochastic Configuration Networks for Modelling Nonlinear Dynamic Systems—0
IndMask: Inductive Explanation for Multivariate Time Series Black-Box ModelsCode0
ExoTST: Exogenous-Aware Temporal Sequence Transformer for Time Series Prediction—0
Spectrum Prediction via Graph Structure LearningCode0
AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction—0
GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets—0
Optimizing Time Series Forecasting: A Comparative Study of Adam and Nesterov Accelerated Gradient on LSTM and GRU networks Using Stock Market dataCode0
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Benchmark Results

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