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 91–100 of 477 papers

TitleStatusHype
Langevin-gradient parallel tempering for Bayesian neural learningCode0
LTC-SE: Expanding the Potential of Liquid Time-Constant Neural Networks for Scalable AI and Embedded SystemsCode0
Multi-task Temporal Convolutional Network for Predicting Water Quality SensorCode0
Genetic algorithm-based hyperparameter optimization of deep learning models for PM2.5 time-series predictionCode0
Generalized Prompt Tuning: Adapting Frozen Univariate Time Series Foundation Models for Multivariate Healthcare Time SeriesCode0
Function Extrapolation with Neural Networks and Its Application for ManifoldsCode0
Hybridizing Traditional and Next-Generation Reservoir Computing to Accurately and Efficiently Forecast Dynamical SystemsCode0
Imbedding Deep Neural NetworksCode0
Time-Series Event Prediction with Evolutionary State GraphCode0
Graph Edit NetworksCode0
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Benchmark Results

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