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 61–70 of 477 papers

TitleStatusHype
A Review of Graph Neural Networks and Their Applications in Power SystemsCode1
Deep Switching Auto-Regressive Factorization:Application to Time Series ForecastingCode1
Adaptive Graph Convolutional Recurrent Network for Traffic ForecastingCode1
Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task LearningCode1
Low-Rank Autoregressive Tensor Completion for Multivariate Time Series ForecastingCode1
Reservoir Computing meets Recurrent Kernels and Structured TransformsCode1
Deep Stock PredictionsCode1
DAG-Net: Double Attentive Graph Neural Network for Trajectory ForecastingCode1
From Fourier to Koopman: Spectral Methods for Long-term Time Series PredictionCode1
Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure EvolutionCode1
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All datasetsData Collected with Package Delivery Quadcopter DroneSunspot

Benchmark Results

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