by Sakif Hossain, Fatema T. Johora, Jørg P. Müller and Sven Hartmann and Andreas Reinhardt
Reference:
SFMGNet: A Physics-Based Neural Network To Predict Pedestrian Trajectories (Sakif Hossain, Fatema T. Johora, Jørg P. Müller and Sven Hartmann and Andreas Reinhardt), In Proceedings of the AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022), Stanford University, Palo Alto, California, USA, March 21-23, 2022 (Andreas Martin et. al., ed.), CEUR-WS.org, volume 3121, 2022.
Bibtex Entry:
@inproceedings{Hossain+2022aaaimake,
	author = {Sakif Hossain and Fatema T. Johora and J{\o}rg P. M{\"u}ller and Sven Hartmann and	Andreas Reinhardt},
	editor = {Andreas Martin et.~al.},
	title  = {SFMGNet: {A} Physics-Based Neural Network To Predict Pedestrian Trajectories},
	booktitle = {Proceedings of the {AAAI} 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence {(AAAI-MAKE} 2022),
	Stanford University, Palo Alto, California, USA, March 21-23, 2022},
	series    = {{CEUR} Workshop Proceedings},
	volume    = {3121},
	publisher = {CEUR-WS.org},
	year      = {2022},
	url       = {http://ceur-ws.org/Vol-3121/paper14.pdf},
}
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