most citedLearning spatiotemporal features from incomplete data for traffic flow prediction using hybrid deep neural networks

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

cs.LG2022★ 2 cited

Learning spatiotemporal features from incomplete data for traffic flow prediction using hybrid deep neural networks

Mehdi Mehdipour Ghazi, Amin Ramezani, Mehdi Siahi +1

Urban traffic flow prediction using data-driven models can play an important role in route planning and preventing congestion on highways. These methods utilize data collected from…

cs.LG2021

CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data

Mostafa Mehdipour Ghazi, Lauge Sørensen, Sébastien Ourselin +1

Learning temporal patterns from multivariate longitudinal data is challenging especially in cases when data is sporadic, as often seen in, e.g., healthcare applications where the d…