1. Wasserstein generative adversarial networks;Arjovsky;Int. Conf. Mach. Learn.,2017
2. Traffic dynamics: Studies in car following;Chandler;Oper. Res.,1958
3. Generative adversarial networks: An overview;Creswell;IEEE Signal Proc. Mag.,2018
4. Gal, Y., Ghahramani, Z., 2016. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. in Proc. Int. Conf. on Mach. Learn. 48, 1050-1059.
5. A behavioural car-following model for computer simulation;Gipps;Transp. Res. B, Methodol.,1981