Deep Learning for Road Traffic Forecasting: Does it Make a Difference?

2 December 2020

Papers citing "Deep Learning for Road Traffic Forecasting: Does it Make a Difference?"

8 / 8 papers shown

Title
A comparative study of deep learning and ensemble learning to extend the horizon of traffic forecasting Xiao Zheng Saeed Asadi Bagloee Majid Sarvi AI4TS 36 0 0 30 Apr 2025
DSTCGCN: Learning Dynamic Spatial-Temporal Cross Dependencies for Traffic Forecasting Binqing Wu Ling-Hao Chen GNN AI4TS 20 3 0 02 Jul 2023
Inverting the Fundamental Diagram and Forecasting Boundary Conditions: How Machine Learning Can Improve Macroscopic Models for Traffic Flow Maya Briani E. Cristiani Elia Onofri 26 2 0 21 Mar 2023
Traffic4cast at NeurIPS 2022 -- Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors M. Neun Christian Eichenberger Henry Martin M. Spanring Rahul Siripurapu ... Kevin Malm Fei Tang Michael K Kopp David P. Kreil Sepp Hochreiter 16 7 0 14 Mar 2023
Measuring the Confidence of Traffic Forecasting Models: Techniques, Experimental Comparison and Guidelines towards Their Actionability I. Laña Ignacio I. Olabarrieta Javier Del Ser 32 1 0 28 Oct 2022
Incorporating dynamicity of transportation network with multi-weight traffic graph convolutional network for traffic forecasting Y. Shin Yoonjin Yoon AI4TS 42 57 0 16 Sep 2019
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 241 3,236 0 24 Nov 2016
Aggregated Residual Transformations for Deep Neural Networks Saining Xie Ross B. Girshick Piotr Dollár Z. Tu Kaiming He 297 10,216 0 16 Nov 2016