2 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.DC2021★ 2 cited
Quasi-Dynamic Traffic Assignment using High Performance Computing
Cy Chan, Anu Kuncheria, Bingyu Zhao +5
Traffic assignment methods are some of the key approaches used to model flow patterns that arise in transportation networks. Since static traffic assignment does not have a notion…
cs.LG2020★ 1 cited
Transfer Learning with Graph Neural Networks for Short-Term Highway Traffic Forecasting
Tanwi Mallick, Prasanna Balaprakash, Eric Rask +1
Highway traffic modeling and forecasting approaches are critical for intelligent transportation systems. Recently, deep-learning-based traffic forecasting methods have emerged as s…
cs.LG2019
Graph-Partitioning-Based Diffusion Convolutional Recurrent Neural Network for Large-Scale Traffic Forecasting
Tanwi Mallick, Prasanna Balaprakash, Eric Rask +1
Traffic forecasting approaches are critical to developing adaptive strategies for mobility. Traffic patterns have complex spatial and temporal dependencies that make accurate forec…