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Implicit Neural Representations (INRs) have recently advanced the field of deep learning due to their ability to learn continuous representations of signals without the need for large training datasets. Although INR methods have been studied for medi
Externí odkaz:
http://arxiv.org/abs/2409.01013
Publikováno v:
Revista da Faculdade de Letras: História. 2023, Vol. 13 Issue 2, p192-195. 4p.
Autor:
Chen, Shuangyi, Khisti, Ashish
In the context of prediction-as-a-service, concerns about the privacy of the data and the model have been brought up and tackled via secure inference protocols. These protocols are built up by using single or multiple cryptographic tools designed und
Externí odkaz:
http://arxiv.org/abs/2404.16232
Autor:
COWPER-COLES, PATRICIO1 pcowpercoles@gmail.com, TRIGO, CAROLINA B.2,3, ANDRADE-DİAZ, MARİA S.4, GÓMEZ, CARLOS2,5,6, TÁLAMO, ANDRÉS2,3,5
Publikováno v:
Ecologia Austral. dic2024, Vol. 34 Issue 3, p486-495. 12p.
Autor:
Ramírez, Ramsés E.1 (AUTHOR) ramses.ramirez@correo.buap.mx, Buendia-Corona, Ricardo E.1 (AUTHOR) ricardo.buendia96@gmail.com, Pérez-Xochipa, Ivonne2 (AUTHOR) ivonne.perez@correo.buap.mx, Scior, Thomas3 (AUTHOR) thomas.scior@correo.buap.mx
Publikováno v:
Molecules. Apr2024, Vol. 29 Issue 7, p1628. 12p.
Publikováno v:
In Chinese Chemical Letters January 2025 36(1)