{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,31]],"date-time":"2025-12-31T12:09:03Z","timestamp":1767182943207,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":31,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,11,30]],"date-time":"2021-11-30T00:00:00Z","timestamp":1638230400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Bundesministerium f\u00fcr Wirtschaft und Energie","award":["19A19005C"],"award-info":[{"award-number":["19A19005C"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,30]]},"DOI":"10.1145\/3488904.3493381","type":"proceedings-article","created":{"date-parts":[[2021,11,25]],"date-time":"2021-11-25T17:08:01Z","timestamp":1637860081000},"page":"1-9","source":"Crossref","is-referenced-by-count":3,"title":["Real-time Uncertainty Estimation Based On Intermediate Layer Variational Inference"],"prefix":"10.1145","author":[{"given":"Ahmed","family":"Hammam","sequence":"first","affiliation":[{"name":"Stellantis, Opel Automobile GmbH, Germany and Karlsruhe Institute of Technology, Institute of Measurement and Control Systems, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Seyed Eghbal","family":"Ghobadi","sequence":"additional","affiliation":[{"name":"Stellantis, Opel Automobile GmbH, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank","family":"Bonarens","sequence":"additional","affiliation":[{"name":"Stellantis, Opel Automobile GmbH, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christoph","family":"Stiller","sequence":"additional","affiliation":[{"name":"Karlsruhe Institute of Technology, Institute of Measurement and Control Systems, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,11,30]]},"reference":[{"volume-title":"A review of uncertainty quantification in deep learning: Techniques, applications and challenges. Information Fusion","year":"2021","author":"Abdar Moloud","key":"e_1_3_2_1_1_1"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2807385"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1285773"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"e_1_3_2_1_7_1","unstructured":"Yarin Gal. 2016. Uncertainty in deep learning. (2016).  Yarin Gal. 2016. Uncertainty in deep learning. (2016)."},{"volume-title":"international conference on machine learning. PMLR, 1050\u20131059","year":"2016","author":"Gal Yarin","key":"e_1_3_2_1_8_1"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00355"},{"volume-title":"Mohsin Ali, Jongseok Lee, Matthias Humt, Jianxiang Feng, Anna Kruspe, Rudolph Triebel","year":"2021","author":"Gawlikowski Jakob","key":"e_1_3_2_1_10_1"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2389824"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_14_1","unstructured":"Alex Kendall and Yarin Gal. 2017. What uncertainties do we need in bayesian deep learning for computer vision?arXiv preprint arXiv:1703.04977(2017).  Alex Kendall and Yarin Gal. 2017. What uncertainties do we need in bayesian deep learning for computer vision?arXiv preprint arXiv:1703.04977(2017)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"e_1_3_2_1_16_1","unstructured":"Diederik\u00a0P Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114(2013).  Diederik\u00a0P Kingma and Max Welling. 2013. Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114(2013)."},{"volume-title":"On information and sufficiency. The annals of mathematical statistics 22, 1","year":"1951","author":"Kullback Solomon","key":"e_1_3_2_1_17_1"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00171"},{"key":"e_1_3_2_1_19_1","unstructured":"Balaji Lakshminarayanan Alexander Pritzel and Charles Blundell. 2016. Simple and scalable predictive uncertainty estimation using deep ensembles. arXiv preprint arXiv:1612.01474(2016).  Balaji Lakshminarayanan Alexander Pritzel and Charles Blundell. 2016. Simple and scalable predictive uncertainty estimation using deep ensembles. arXiv preprint arXiv:1612.01474(2016)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.zemedi.2018.11.002"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01216-8_12"},{"key":"e_1_3_2_1_24_1","unstructured":"John Mitros and Brian Mac\u00a0Namee. 2019. On the validity of Bayesian neural networks for uncertainty estimation. arXiv preprint arXiv:1912.01530(2019).  John Mitros and Brian Mac\u00a0Namee. 2019. On the validity of Bayesian neural networks for uncertainty estimation. arXiv preprint arXiv:1912.01530(2019)."},{"key":"e_1_3_2_1_25_1","unstructured":"Jishnu Mukhoti and Yarin Gal. 2018. Evaluating bayesian deep learning methods for semantic segmentation. arXiv preprint arXiv:1811.12709(2018).  Jishnu Mukhoti and Yarin Gal. 2018. Evaluating bayesian deep learning methods for semantic segmentation. arXiv preprint arXiv:1811.12709(2018)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.5555\/2888116.2888120"},{"key":"e_1_3_2_1_27_1","unstructured":"Lukas Neumann Andrew Zisserman and Andrea Vedaldi. 2018. Relaxed softmax: Efficient confidence auto-calibration for safe pedestrian detection. (2018).  Lukas Neumann Andrew Zisserman and Andrea Vedaldi. 2018. Relaxed softmax: Efficient confidence auto-calibration for safe pedestrian detection. (2018)."},{"key":"e_1_3_2_1_28_1","unstructured":"Yaniv Ovadia Emily Fertig Jie Ren Zachary Nado David Sculley Sebastian Nowozin Joshua\u00a0V Dillon Balaji Lakshminarayanan and Jasper Snoek. 2019. Can you trust your model\u2019s uncertainty? Evaluating predictive uncertainty under dataset shift. arXiv preprint arXiv:1906.02530(2019).  Yaniv Ovadia Emily Fertig Jie Ren Zachary Nado David Sculley Sebastian Nowozin Joshua\u00a0V Dillon Balaji Lakshminarayanan and Jasper Snoek. 2019. Can you trust your model\u2019s uncertainty? Evaluating predictive uncertainty under dataset shift. arXiv preprint arXiv:1906.02530(2019)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.10.315"},{"key":"e_1_3_2_1_30_1","unstructured":"Joseph Redmon and Ali Farhadi. 2018. Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767(2018).  Joseph Redmon and Ali Farhadi. 2018. Yolov3: An incremental improvement. arXiv preprint arXiv:1804.02767(2018)."},{"volume-title":"Deep high-resolution representation learning for visual recognition","year":"2020","author":"Wang Jingdong","key":"e_1_3_2_1_31_1"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2706963"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-55583-2_25"},{"volume-title":"Human-like autonomous car-following model with deep reinforcement learning. Transportation research part C: emerging technologies 97","year":"2018","author":"Zhu Meixin","key":"e_1_3_2_1_34_1"}],"event":{"name":"CSCS '21: Computer Science in Cars Symposium","sponsor":["SIGGRAPH ACM Special Interest Group on Computer Graphics and Interactive Techniques"],"location":"Ingolstadt Germany","acronym":"CSCS '21"},"container-title":["Computer Science in Cars Symposium"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488904.3493381","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3488904.3493381","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:48:28Z","timestamp":1750193308000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3488904.3493381"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,30]]},"references-count":31,"alternative-id":["10.1145\/3488904.3493381","10.1145\/3488904"],"URL":"https:\/\/doi.org\/10.1145\/3488904.3493381","relation":{},"subject":[],"published":{"date-parts":[[2021,11,30]]}}}