{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:28:57Z","timestamp":1743143337643,"version":"3.40.3"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031687372"},{"type":"electronic","value":"9783031687389"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-68738-9_29","type":"book-chapter","created":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T23:02:40Z","timestamp":1725836560000},"page":"365-378","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enclosing Prototypical Variational Autoencoder for\u00a0Explainable Out-of-Distribution Detection"],"prefix":"10.1007","author":[{"given":"Conrad","family":"Orglmeister","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"Bochinski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Volker","family":"Eiselein","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elvira","family":"Fleig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,9]]},"reference":[{"key":"29_CR1","unstructured":"Bercea, C., Rueckert, D., Schnabel, J.: What do we learn? Debunking the myth of unsupervised outlier detection. arXiv preprint arXiv:2206.03698 (2022)"},{"key":"29_CR2","unstructured":"Chen, G., Peng, P., Wang, X., Tian, Y.: Adversarial reciprocal points learning for open set recognition. In: TPAMI, pp. 8065\u20138081 (2022)"},{"key":"29_CR3","unstructured":"Denouden, T., Salay, R., Czarnecki, K., Abdelzad, V., Phan, B., Vernekar, S.: Improving reconstruction autoencoder out-of-distribution detection with Mahalanobis distance. arXiv preprint arXiv:1812.02765 (2018)"},{"key":"29_CR4","unstructured":"Digitale Schiene Deutschland: https:\/\/www.digitale-schiene-deutschland.de\/en\/. Accessed 07 Jun 2024"},{"key":"29_CR5","unstructured":"Du, X., Gozum, G., Ming, Y., Li, Y.: Siren: shaping representations for detecting out-of-distribution objects. In: NeurIPS, vol.\u00a035, pp. 20434\u201320449 (2022)"},{"key":"29_CR6","unstructured":"Fiack, A., Weller, F., Heimes, M., Laux, T.: Digitale Schiene Deutschland - Zukunftstechnologien f\u00fcr das Bahnsystem. EIK 2024 (2024)"},{"key":"29_CR7","unstructured":"Gal, Y., Ghahramani, Z.: Dropout as a Bayesian approximation: Representing model uncertainty in deep learning. In: ICML, pp. 1050\u20131059 (2016)"},{"key":"29_CR8","unstructured":"Gautam, S., et al.: ProtoVAE: a trustworthy self-explainable prototypical variational model. In: NeurIPS, pp. 17940\u201317952 (2022)"},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Graham, M.S., Pinaya, W.H.L., Tudosiu, P.D., Nachev, P., Ourselin, S., Cardoso, M.J.: Denoising diffusion models for out-of-distribution detection. In: CVPR Workshops, pp. 2948\u20132957 (2023)","DOI":"10.1109\/CVPRW59228.2023.00296"},{"key":"29_CR10","unstructured":"Guo, C., Pleiss, G., Sun, Y., Weinberger, K.Q.: On calibration of modern neural networks. In: ICML, pp. 1321\u20131330 (2017)"},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: CVPR, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"29_CR12","unstructured":"Hendrycks, D., et al.: Scaling out-of-distribution detection for real-world settings. In: ICML, pp. 8759\u20138773 (2022)"},{"key":"29_CR13","unstructured":"Hendrycks, D., Gimpel, K.: A baseline for detecting misclassified and out-of-distribution examples in neural networks. In: ICLR (2017)"},{"key":"29_CR14","doi-asserted-by":"crossref","unstructured":"Hendrycks, D., et al.: PixMix: dreamlike pictures comprehensively improve safety measures. In: CVPR, pp. 16762\u201316771 (2022)","DOI":"10.1109\/CVPR52688.2022.01628"},{"key":"29_CR15","unstructured":"Lakshminarayanan, B., Pritzel, A., Blundell, C.: Simple and scalable predictive uncertainty estimation using deep ensembles. In: NIPS, pp. 6405\u20136416 (2017)"},{"key":"29_CR16","unstructured":"Lee, K., Lee, K., Lee, H., Shin, J.: A simple unified framework for detecting out-of-distribution samples and adversarial attacks. In: NeurIPS, pp. 7167\u20137177 (2018)"},{"key":"29_CR17","unstructured":"Nalisnick, E., Matsukawa, A., Teh, Y.W., Gorur, D., Lakshminarayanan, B.: Do deep generative models know what they don\u2019t know? In: ICLR (2019)"},{"key":"29_CR18","doi-asserted-by":"crossref","unstructured":"Oza, P., Patel, V.M.: C2AE: class conditioned auto-encoder for open-set recognition. In: CVPR, pp. 2307\u20132316 (2019)","DOI":"10.1109\/CVPR.2019.00241"},{"key":"29_CR19","unstructured":"Ruff, L., et al.: Deep one-class classification. In: ICML, pp. 4393\u20134402 (2018)"},{"key":"29_CR20","doi-asserted-by":"crossref","unstructured":"Shi, W., et al.: Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network. In: CVPR, pp. 1874\u20131883 (2016)","DOI":"10.1109\/CVPR.2016.207"},{"key":"29_CR21","doi-asserted-by":"crossref","unstructured":"Sun, X., Yang, Z., Zhang, C., Ling, K.V., Peng, G.: Conditional gaussian distribution learning for open set recognition. In: CVPR, pp. 13477\u201313486 (2020)","DOI":"10.1109\/CVPR42600.2020.01349"},{"key":"29_CR22","unstructured":"Sun, Y., Guo, C., Li, Y.: React: out-of-distribution detection with rectified activations. In: NeurIPS, pp. 144\u2013157 (2021)"},{"key":"29_CR23","unstructured":"Sun, Y., Ming, Y., Zhu, X., Li, Y.: Out-of-distribution detection with deep nearest neighbors. In: ICML, pp. 20827\u201320840 (2022)"},{"key":"29_CR24","doi-asserted-by":"crossref","unstructured":"Wang, H., Li, Z., Feng, L., Zhang, W.: ViM: out-of-distribution with virtual-logit matching. In: CVPR, pp. 4921\u20134930 (2022)","DOI":"10.1109\/CVPR52688.2022.00487"},{"key":"29_CR25","unstructured":"Xiao, Z., Yan, Q., Amit, Y.: Likelihood regret: an out-of-distribution detection score for variational auto-encoder. In: NeurIPS, pp. 20685\u201320696 (2020)"},{"key":"29_CR26","unstructured":"Yang, J., et\u00a0al.: OpenOOD: benchmarking generalized out-of-distribution detection. In: NeurIPS, pp. 32598\u201332611 (2022)"},{"key":"29_CR27","unstructured":"Yang, J., Zhou, K., Li, Y., Liu, Z.: Generalized out-of-distribution detection: a survey. arXiv preprint arXiv:2110.11334 (2021)"},{"key":"29_CR28","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: CVPR, pp. 586\u2013595 (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"29_CR29","doi-asserted-by":"crossref","unstructured":"Zhou, Y.: Rethinking reconstruction autoencoder-based out-of-distribution detection. In: CVPR, pp. 7369\u20137377 (2022)","DOI":"10.1109\/CVPR52688.2022.00723"}],"container-title":["Lecture Notes in Computer Science","Computer Safety, Reliability, and Security. SAFECOMP 2024 Workshops"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-68738-9_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T23:09:33Z","timestamp":1725836973000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-68738-9_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031687372","9783031687389"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-68738-9_29","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"9 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SAFECOMP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Safety, Reliability, and Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Florence","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"43","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"safecomp2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.safecomp2024.unifi.it\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}