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Greatest papers with code

Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning

KDD '19 2019 panzheyi/ST-MetaNet

Predicting urban traffic is of great importance to intelligent transportation systems and public safety, yet is very challenging because of two aspects: 1) complex spatio-temporal correlations of urban traffic, including spatial correlations between locations along with temporal correlations among timestamps; 2) diversity of such spatiotemporal correlations, which vary from location to location and depend on the surrounding geographical information, e. g., points of interests and road networks.

META-LEARNING SPATIO-TEMPORAL FORECASTING TIME SERIES TRAFFIC PREDICTION

Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting

24 Jul 2017amirstar/Deep-Forecast

The paper presents a spatio-temporal wind speed forecasting algorithm using Deep Learning (DL)and in particular, Recurrent Neural Networks(RNNs).

SPATIO-TEMPORAL FORECASTING TIME SERIES

Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting

NeurIPS 2020 LeiBAI/AGCRN

We further propose an Adaptive Graph Convolutional Recurrent Network (AGCRN) to capture fine-grained spatial and temporal correlations in traffic series automatically based on the two modules and recurrent networks.

GRAPH GENERATION MULTIVARIATE TIME SERIES FORECASTING SPATIO-TEMPORAL FORECASTING TIME SERIES TIME SERIES PREDICTION TRAFFIC PREDICTION

Deep Integro-Difference Equation Models for Spatio-Temporal Forecasting

29 Oct 2019andrewzm/deepIDE

Both procedures tend to be excellent for prediction purposes over small time horizons, but are generally time-consuming and, crucially, do not provide a global prior model for the temporally-varying dynamics that is realistic.

SPATIO-TEMPORAL FORECASTING

A Spatio-Temporal Spot-Forecasting Framework for Urban Traffic Prediction

31 Mar 2020rdemedrano/crann_traffic

Spatio-temporal forecasting is an open research field whose interest is growing exponentially.

SPATIO-TEMPORAL FORECASTING TIME SERIES TRAFFIC PREDICTION

Active machine learning for spatio-temporal predictions using feature embedding

8 Dec 2020ArsamAryandoust/ActiveLearning

Active learning (AL) could contribute to solving critical environmental problems through improved spatio-temporal predictions.

ACTIVE LEARNING SPATIO-TEMPORAL FORECASTING