{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:13:02Z","timestamp":1750219982353,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":18,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,11]]},"DOI":"10.1145\/3557915.3560940","type":"proceedings-article","created":{"date-parts":[[2022,11,23]],"date-time":"2022-11-23T00:11:25Z","timestamp":1669162285000},"page":"1-4","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["An adversarial variational inference approach for travel demand calibration of urban traffic simulators"],"prefix":"10.1145","author":[{"given":"Martin","family":"Mladenov","sequence":"first","affiliation":[{"name":"Google Research"}]},{"given":"Sanjay Ganapathy","family":"Subramaniam","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Chih-wei","family":"Hsu","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Neha","family":"Arora","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Andrew","family":"Tomkins","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Craig","family":"Boutilier","sequence":"additional","affiliation":[{"name":"Google Research"}]},{"given":"Carolina","family":"Osorio","sequence":"additional","affiliation":[{"name":"Google Research"}]}],"member":"320","published-online":{"date-parts":[[2022,11,22]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"M. Abadi A. Agarwal P. Barham E. Brevdo Z. Chen C. Citro G. S. Corrado A. Davis J. Dean M. Devin S. Ghemawat I. Goodfellow A. Harp G. Irving M. Isard Y. Jia R. Jozefowicz L. Kaiser M. Kudlur J. Levenberg D. Man\u00e9 R. Monga S. Moore D. Murray C. Olah M. Schuster J. Shlens B. Steiner I. Sutskever K. Talwar P. Tucker V. Vanhoucke V. Vasudevan F. Vi\u00e9gas O. Vinyals P. Warden M. Wattenberg M. Wicke Y. Yu and X. Zheng. 2015. TensorFlow: Large-scale Machine Learning on Heterogeneous Systems."},{"key":"e_1_3_2_1_2_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning, ICML 2017","volume":"70","author":"Arjovsky M.","year":"2017","unstructured":"M. Arjovsky, S. Chintala, and L\u00e9on Bottou. 2017. Wasserstein Generative Adversarial Networks. In Proceedings of the 34th International Conference on Machine Learning, ICML 2017, Sydney, NSW, Australia, Vol. 70. 214--223."},{"key":"e_1_3_2_1_3_1","unstructured":"N. Arora T. Cabannes S. Ganapathy Y. Li P. McAfee M. Nunkesser C. Osorio A. Tomkins and I. Tsogsuren. 2021. Quantifying the sustainability impact of Google Maps: A case study of Salt Lake City. https:\/\/arxiv.org\/abs\/2111.03426."},{"key":"e_1_3_2_1_4_1","unstructured":"N. Arora Y. Chen S. Ganapathy Y. Li Z. Lin C. Osorio A. Tomkins and I. Tsogsuren. 2021. An Efficient Simulation-Based Travel Demand Calibration Algorithm for Large-Scale Metropolitan Traffic Models. https:\/\/arxiv.org\/abs\/2109.11392."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2910295"},{"key":"e_1_3_2_1_6_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems","author":"Heusel M.","year":"2017","unstructured":"M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter. 2017. GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, Long Beach, CA, USA. 6626--6637."},{"key":"e_1_3_2_1_7_1","unstructured":"J. Jin D. Rong T. Zhang Q. Ji H. Guo Y. Lv X. Ma and F. Wang. 2022. A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework. IEEE Transactions on Intelligent Transportation Systems (2022) 1--12."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2019.05.014"},{"volume-title":"21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2575--2582","author":"Lopez P.","key":"e_1_3_2_1_9_1","unstructured":"P. Lopez, M. Behrisch, L. Bieker-Walz, J. Erdmann, Y. Fl\u00f6tter\u00f6d, R. Hilbrich, L. L\u00fccken, J. Rummel, P. Wagner, and E. Wie\u00dfner. 2018. Microscopic traffic simulation using SUMO. In 21st International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2575--2582."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"M. Mladenov C. Hsu V. Jain E. Ie C. Colby N. Mayoraz H. Pham D. Tran I. Vendrov and C. Boutilier. 2021. RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems. Technical Report. arXiv:2103.08057 [cs.LG]","DOI":"10.1145\/3383313.3411527"},{"key":"e_1_3_2_1_11_1","volume-title":"Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems","author":"Nowozin S.","year":"2016","unstructured":"S. Nowozin, B. Cseke, and R. Tomioka. 2016. f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, Barcelona, Spain. 271--279."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2018.09.023"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2019.01.005"},{"key":"e_1_3_2_1_14_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017","author":"Roth K.","year":"2018","unstructured":"K. Roth, A. Lucchi, S. Nowozin, and T. Hofmann. 2017. Stabilizing Training of Generative Adversarial Networks through Regularization. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, Long Beach, CA, USA. 2018--2028."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","unstructured":"L. Schultz and V. Sokolov. 2018. Practical Bayesian Optimization for Transportation Simulators. 10.48550\/ARXIV.1810.03688","DOI":"10.48550\/ARXIV.1810.03688"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1177\/0361198120936252"},{"volume-title":"Introduction to stochastic search and optimization: estimation, simulation, and control","author":"Spall J.","key":"e_1_3_2_1_17_1","unstructured":"J. Spall. 2003. Introduction to stochastic search and optimization: estimation, simulation, and control. John Wiley & Sons, New Jersey, USA."},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2955794"}],"event":{"name":"SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems","sponsor":["SIGSPATIAL ACM Special Interest Group on Spatial Information"],"location":"Seattle Washington","acronym":"SIGSPATIAL '22"},"container-title":["Proceedings of the 30th International Conference on Advances in Geographic Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3557915.3560940","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3557915.3560940","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:26Z","timestamp":1750182566000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3557915.3560940"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11]]},"references-count":18,"alternative-id":["10.1145\/3557915.3560940","10.1145\/3557915"],"URL":"https:\/\/doi.org\/10.1145\/3557915.3560940","relation":{},"subject":[],"published":{"date-parts":[[2022,11]]},"assertion":[{"value":"2022-11-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}