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Spatio-Temporal Forecasting

4 papers with code ยท Time Series

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CGT: Clustered Graph Transformer for Urban Spatio-temporal Prediction

ICLR 2020

Deep learning based approaches have been widely used in various urban spatio-temporal forecasting problems, but most of them fail to account for the unsmoothness issue of urban data in their architecture design, which significantly deteriorates their prediction performance.

SPATIO-TEMPORAL FORECASTING TIME SERIES

HyperST-Net: Hypernetworks for Spatio-Temporal Forecasting

28 Sep 2018

In this paper, we propose a general framework (HyperST-Net) based on hypernetworks for deep ST models.

SPATIO-TEMPORAL FORECASTING TIME SERIES

Deep Echo State Networks with Uncertainty Quantification for Spatio-Temporal Forecasting

28 Jun 2018

The first approach utilizes a bootstrap ensemble framework and the second is developed within a hierarchical Bayesian framework (BD-EESN).

SPATIO-TEMPORAL FORECASTING

Gini-regularized Optimal Transport with an Application to Spatio-Temporal Forecasting

7 Dec 2017

Moreover, we show that the Gini regularized OT problem converges to the classical OT problem, when the Gini regularized problem is considered as a function of {\lambda}, the regularization parame-ter.

SPATIO-TEMPORAL FORECASTING

Bayesian Recurrent Neural Network Models for Forecasting and Quantifying Uncertainty in Spatial-Temporal Data

2 Nov 2017

Recurrent neural networks (RNNs) are nonlinear dynamical models commonly used in the machine learning and dynamical systems literature to represent complex dynamical or sequential relationships between variables.

SPATIO-TEMPORAL FORECASTING

An Ensemble Quadratic Echo State Network for Nonlinear Spatio-Temporal Forecasting

16 Aug 2017

Spatio-temporal data and processes are prevalent across a wide variety of scientific disciplines.

SPATIO-TEMPORAL FORECASTING