Inproceedings,
Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors.
M. Neun, C. Eichenberger, H. Martin, M. Spanring, R. Siripurapu, D. Springer, L. Deng, C. Wu, D. Lian, M. Zhou, M. Lumiste, A. Ilie, X. Wu, C. Lyu, Q. Lu, V. Mahajan, Y. Lu, J. Li, J. Li, Y. Gong, F. Grötschla, J. Mathys, Y. Wei, H. Haitao, H. Fang, K. Malm, F. Tang, M. Kopp, D. Kreil, and S. Hochreiter.NeurIPS (Competition and Demos), volume 220 of Proceedings of Machine Learning Research, page 251-278. PMLR, (2021)
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- BibTeX key
- conf/nips/NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21
- entry type
- inproceedings
- booktitle
- NeurIPS (Competition and Demos)
- year
- 2021
- pages
- 251-278
- publisher
- PMLR
- series
- Proceedings of Machine Learning Research
- volume
- 220
- crossref
- conf/nips/2022demo
- ee
- https://proceedings.mlr.press/v220/neun22a.html
- url
- http://dblp.uni-trier.de/db/conf/nips/demo2022.html#NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21
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- please select -%0 Conference Paper
%1 conf/nips/NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21
%A Neun, Moritz
%A Eichenberger, Christian
%A Martin, Henry
%A Spanring, Markus
%A Siripurapu, Rahul
%A Springer, Daniel
%A Deng, Leyan
%A Wu, Chenwang
%A Lian, Defu
%A Zhou, Min
%A Lumiste, Martin
%A Ilie, Andrei
%A Wu, Xinhua
%A Lyu, Cheng
%A Lu, Qing-Long
%A Mahajan, Vishal
%A Lu, Yichao
%A Li, Jiezhang
%A Li, Junjun
%A Gong, Yue-Jiao
%A Grötschla, Florian
%A Mathys, Joël
%A Wei, Ye
%A Haitao, He
%A Fang, Hui
%A Malm, Kevin
%A Tang, Fei
%A Kopp, Michael
%A Kreil, David P.
%A Hochreiter, Sepp
%B NeurIPS (Competition and Demos)
%D 2021
%E Ciccone, Marco
%E Stolovitzky, Gustavo
%E Albrecht, Jacob
%I PMLR
%K dblp
%P 251-278
%T Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors.
%U http://dblp.uni-trier.de/db/conf/nips/demo2022.html#NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21
%V 220
@inproceedings{conf/nips/NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21,
added-at = {2023-12-04T00:00:00.000+0100},
author = {Neun, Moritz and Eichenberger, Christian and Martin, Henry and Spanring, Markus and Siripurapu, Rahul and Springer, Daniel and Deng, Leyan and Wu, Chenwang and Lian, Defu and Zhou, Min and Lumiste, Martin and Ilie, Andrei and Wu, Xinhua and Lyu, Cheng and Lu, Qing-Long and Mahajan, Vishal and Lu, Yichao and Li, Jiezhang and Li, Junjun and Gong, Yue-Jiao and Grötschla, Florian and Mathys, Joël and Wei, Ye and Haitao, He and Fang, Hui and Malm, Kevin and Tang, Fei and Kopp, Michael and Kreil, David P. and Hochreiter, Sepp},
biburl = {https://www.bibsonomy.org/bibtex/2972526099c26d12038f943db447fd49d/dblp},
booktitle = {NeurIPS (Competition and Demos)},
crossref = {conf/nips/2022demo},
editor = {Ciccone, Marco and Stolovitzky, Gustavo and Albrecht, Jacob},
ee = {https://proceedings.mlr.press/v220/neun22a.html},
interhash = {13cfa9a530f1d91ef2b6f6cb784349dd},
intrahash = {972526099c26d12038f943db447fd49d},
keywords = {dblp},
pages = {251-278},
publisher = {PMLR},
series = {Proceedings of Machine Learning Research},
timestamp = {2024-04-09T23:11:25.000+0200},
title = {Traffic4cast at NeurIPS 2022 – Predict Dynamics along Graph Edges from Sparse Node Data: Whole City Traffic and ETA from Stationary Vehicle Detectors.},
url = {http://dblp.uni-trier.de/db/conf/nips/demo2022.html#NeunEMSSSDWLZLIWLLMLLLGGMWHFMTKKH21},
volume = 220,
year = 2021
}