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Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

X. Bai, H. Wang, L. Ma, Y. Xu, J. Gan, Z. Fan, F. Yang, K. Ma, J. Yang, S. Bai, C. Shu, X. Zou, R. Huang, C. Zhang, X. Liu, D. Tu, C. Xu, W. Zhang, X. Wang, A. Chen, Y. Zeng, D. Yang, M. Wang, N. Holalkere, N. Halin, I. Kamel, J. Wu, X. Peng, X. Wang, J. Shao, P. Mongkolwat, J. Zhang, W. Liu, M. Roberts, Z. Teng, L. Beer, L. Sanchez, E. Sala, D. Rubin, A. Weller, J. Lasenby, C. Zheng, J. Wang, Z. Li, C. Schönlieb, and T. Xia. CoRR, (2021)

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Bibiane Erlenkämper

Bibiane Puhl

Bibiane Schwartz-Kraft

Nadine Bibiane Bitzer

Carola Urhausen

Apoptose in der uterotubalen Verbindung und im Eileiteristhmus der Hündin im ZyklusverlaufC. Urhausen. TierH Hannover, (2009)

Other publications of authors with the same name

Dynamic Sampling Schemes for Optimal Noise Learning Under Multiple Nonsmooth Constraints.L. Calatroni, J. de los Reyes, and C. Schönlieb. System Modelling and Optimization, volume 443 of IFIP Advances in Information and Communication Technology, page 85-95. Springer, (2013)Variational regularisation for inverse problems with imperfect forward operators and general noise modelsL. Bungert, M. Burger, Y. Korolev, and C. Schönlieb. Inverse Problems, 36 (12): 125014 (2020)Variational multi-task MRI reconstruction: Joint reconstruction, registration and super-resolution.V. Corona, A. Avilés-Rivero, N. Debroux, C. Guyader, and C. Schönlieb. Medical Image Anal., (2021)Rethinking medical image reconstruction via shape prior, going deeper and faster: Deep joint indirect registration and reconstruction.J. Liu, A. Avilés-Rivero, H. Ji, and C. Schönlieb. Medical Image Anal., (2021)Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans.M. Roberts, D. Driggs, M. Thorpe, J. Gilbey, M. Yeung, S. Ursprung, A. Avilés-Rivero, C. Etmann, C. McCague, L. Beer and 6 other author(s). Nat. Mach. Intell., 3 (3): 199-217 (2021)Deep learning as optimal control problems: models and numerical methods.M. Benning, E. Celledoni, M. Ehrhardt, B. Owren, and C. Schönlieb. CoRR, (2019)Learned reconstruction with convergence guarantees.S. Mukherjee, A. Hauptmann, O. Öktem, M. Pereyra, and C. Schönlieb. CoRR, (2022)Bilevel approaches for learning of variational imaging models.L. Calatroni, C. Chung, J. de los Reyes, C. Schönlieb, and T. Valkonen. CoRR, (2015)Multi-modal learning for predicting the genotype of glioma.Y. Wei, X. Chen, L. Zhu, L. Zhang, C. Schönlieb, S. Price, and C. Li. CoRR, (2022)A Continuous-time Stochastic Gradient Descent Method for Continuous Data.K. Jin, J. Latz, C. Liu, and C. Schönlieb. CoRR, (2021)

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Disambiguation of "Schönlieb, Carola-Bibiane"

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Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Please choose a person to relate this publication to

Bibiane Erlenkämper

Bibiane Puhl

Bibiane Schwartz-Kraft

Nadine Bibiane Bitzer

Carola Urhausen

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Schönlieb, Carola-Bibiane"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.

Please choose a person to relate this publication to

Bibiane Erlenkämper

Bibiane Puhl

Bibiane Schwartz-Kraft

Nadine Bibiane Bitzer

Carola Urhausen

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
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APA
Chicago
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Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence.