{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T15:40:53Z","timestamp":1762443653715,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030504199"},{"type":"electronic","value":"9783030504205"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"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":[[2020]]},"DOI":"10.1007\/978-3-030-50420-5_12","type":"book-chapter","created":{"date-parts":[[2020,6,19]],"date-time":"2020-06-19T11:04:32Z","timestamp":1592564672000},"page":"158-171","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Design of Loss Functions for Solving Inverse Problems Using Deep Learning"],"prefix":"10.1007","author":[{"given":"Jon Ander","family":"Rivera","sequence":"first","affiliation":[]},{"given":"David","family":"Pardo","sequence":"additional","affiliation":[]},{"given":"Elisabete","family":"Alberdi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,6,15]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-1-4612-1878-4_1","volume-title":"Inverse Problems in Wave Propagation","author":"RA Albanese","year":"1997","unstructured":"Albanese, R.A.: Wave propagation inverse problems in medicine and environmental health. In: Chavent, G., Sacks, P., Papanicolaou, G., Symes, W.W. (eds.) Inverse Problems in Wave Propagation, pp. 1\u201311. Springer, New York (1997). https:\/\/doi.org\/10.1007\/978-1-4612-1878-4_1"},{"key":"12_CR2","unstructured":"Beer, R., et al.: Geosteering and\/or reservoir characterization the prowess of new generation LWD tools. 51st Annual Logging Symposium Society of Petrophysicists and Well-Log Analysts (SPWLA) (2010)"},{"issue":"2","key":"12_CR3","doi-asserted-by":"publisher","first-page":"R1","DOI":"10.1088\/0266-5611\/21\/2\/r01","volume":"21","author":"M Bonnet","year":"2005","unstructured":"Bonnet, M., Constantinescu, A.: Inverse problems in elasticity. Inverse Prob. 21(2), R1\u2013R50 (2005). https:\/\/doi.org\/10.1088\/0266-5611\/21\/2\/r01","journal-title":"Inverse Prob."},{"issue":"5","key":"12_CR4","doi-asserted-by":"publisher","first-page":"730","DOI":"10.1109\/8.668918","volume":"46","author":"A Broquetas","year":"1998","unstructured":"Broquetas, A., Palau, J., Jofre, L., Cardama, A.: Spherical wave near-field imaging and radar cross-section measurement. IEEE Trans. Antennas Propag. 46(5), 730\u2013735 (1998)","journal-title":"IEEE Trans. Antennas Propag."},{"key":"12_CR5","doi-asserted-by":"publisher","unstructured":"Burczy\u0144ski, T., Beluch, W., Dugosz, A., Orantek, P., Nowakowski, M.: Evolutionary methods in inverse problems of engineering mechanics. In: Inverse Problems in Engineering Mechanics II, pp. 553\u2013562. Elsevier Science Ltd., Oxford (2000). https:\/\/doi.org\/10.1016\/B978-008043693-7\/50131-8. http:\/\/www.sciencedirect.com\/science\/article\/pii\/B9780080436937501318","DOI":"10.1016\/B978-008043693-7\/50131-8"},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation (2014)","DOI":"10.3115\/v1\/D14-1179"},{"key":"12_CR7","doi-asserted-by":"crossref","unstructured":"Hara, K., Saito, D., Shouno, H.: Analysis of function of rectified linear unit used in deep learning. In: 2015 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138 (2015)","DOI":"10.1109\/IJCNN.2015.7280578"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., van der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017","DOI":"10.1109\/CVPR.2017.243"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Jin, Y., Wu, X., Chen, J., Huang, Y.: Using a physics-driven deep neural network to solve inverse problems for LWD azimuthal resistivity measurements, pp. 1\u201313, June 2019","DOI":"10.30632\/T60ALS-2019_IIII"},{"key":"12_CR10","unstructured":"Li, Q., Omeragic, D., Chou, L., Yang, L., Duong, K.: New directional electromagnetic tool for proactive geosteering and accurate formation evaluation while drilling (2005)"},{"key":"12_CR11","doi-asserted-by":"publisher","unstructured":"Liu, G., Zhou, B., Liao, S.: Inverting methods for thermal reservoir evaluation of enhanced geothermal system. Renew. Sustain. Energy Rev. 82, 471\u2013476 (2018). https:\/\/doi.org\/10.1016\/j.rser.2017.09.065. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1364032117313175","DOI":"10.1016\/j.rser.2017.09.065"},{"key":"12_CR12","unstructured":"Mao, X.J., Shen, C., Yang, Y.B.: Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections (2016)"},{"key":"12_CR13","doi-asserted-by":"publisher","unstructured":"Neto, A.S., Soeiro, F.: Solution of implicitly formulated inverse heat transfer problems with hybrid methods. In: Computational Fluid and Solid Mechanics 2003, pp. 2369\u20132372. Elsevier Science Ltd., Oxford (2003). https:\/\/doi.org\/10.1016\/B978-008044046-0.50582-0","DOI":"10.1016\/B978-008044046-0.50582-0"},{"issue":"2","key":"12_CR14","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1088\/0266-5611\/19\/2\/304","volume":"19","author":"AA Oberai","year":"2003","unstructured":"Oberai, A.A., Gokhale, N.H., Feij\u00f3o, G.R.F.: Solution of inverse problems in elasticity imaging using the adjoint method. Inverse Prob. 19(2), 297\u2013313 (2003). https:\/\/doi.org\/10.1088\/0266-5611\/19\/2\/304","journal-title":"Inverse Prob."},{"key":"12_CR15","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1093\/gji\/ggz204","volume":"218","author":"V Puzyrev","year":"2019","unstructured":"Puzyrev, V.: Deep learning electromagnetic inversion with convolutional neural networks. Geophys. J. Int. 218, 817\u2013832 (2019). https:\/\/doi.org\/10.1093\/gji\/ggz204","journal-title":"Geophys. J. Int."},{"key":"12_CR16","doi-asserted-by":"publisher","first-page":"451","DOI":"10.1017\/S0962492910000061","volume":"19","author":"AM Stuart","year":"2010","unstructured":"Stuart, A.M.: Inverse problems: a Bayesian perspective. Acta Numerica 19, 451\u2013559 (2010). https:\/\/doi.org\/10.1017\/S0962492910000061","journal-title":"Acta Numerica"},{"key":"12_CR17","volume-title":"Inverse Problem Theory and Methods for Model Parameter Estimation","author":"A Tarantola","year":"2004","unstructured":"Tarantola, A.: Inverse Problem Theory and Methods for Model Parameter Estimation. Society for Industrial and Applied Mathematics, USA (2004)"},{"key":"12_CR18","doi-asserted-by":"crossref","unstructured":"Xu, Y., et al.: Schlumberger: Borehole resistivity measurement modeling using machine-learning techniques (2018)","DOI":"10.30632\/PJV59N6-2018a3"},{"key":"12_CR19","doi-asserted-by":"publisher","unstructured":"Zhu, G., Gao, M., Kong, F., Li, K.: A fast inversion of induction logging data in anisotropic formation based on deep learning. IEEE Geosci. Remote Sens. Lett., 1\u20135 (2020). https:\/\/doi.org\/10.1109\/LGRS.2019.2961374","DOI":"10.1109\/LGRS.2019.2961374"}],"container-title":["Lecture Notes in Computer Science","Computational Science \u2013 ICCS 2020"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-50420-5_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T23:18:52Z","timestamp":1718752732000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-50420-5_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030504199","9783030504205"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-50420-5_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"15 June 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Amsterdam","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"The Netherlands","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 June 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccs-computsci2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.iccs-meeting.org\/iccs2020\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"230","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"98","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"43% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2.5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"248 workshop papers were selected from 489 submissions to the thematic tracks. The conference was canceled due to the COVID-19 pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}