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Connections Between Numerical Algorithms for PDEs and Neural Networks.

, , , , and . J. Math. Imaging Vis., 65 (1): 185-208 (January 2023)

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Translating Diffusion, Wavelets, and Regularisation into Residual Networks., , and . CoRR, (2020)Learning a Generic Adaptive Wavelet Shrinkage Function for Denoising., and . ICASSP, page 2018-2022. IEEE, (2020)Connections between Numerical Algorithms for PDEs and Neural Networks., , , , and . CoRR, (2021)Learning Integrodifferential Models for Image Denoising., and . ICASSP, page 2045-2049. IEEE, (2021)Translating Numerical Concepts for PDEs into Neural Architectures., , , and . SSVM, volume 12679 of Lecture Notes in Computer Science, page 294-306. Springer, (2021)Generative AI Models: Opportunities and Risks for Industry and Authorities., , , , , , , , , and 5 other author(s). CoRR, (2024)Connections Between Numerical Algorithms for PDEs and Neural Networks., , , , and . J. Math. Imaging Vis., 65 (1): 185-208 (January 2023)Learning Sparse Masks for Diffusion-Based Image Inpainting., , and . IbPRIA, volume 13256 of Lecture Notes in Computer Science, page 528-539. Springer, (2022)JPEG Meets PDE-based Image Compression., , , and . PCS, page 1-5. IEEE, (2021)CNN-based Euler's Elastica Inpainting with Deep Energy and Deep Image Prior., , , and . EUVIP, page 1-6. IEEE, (2022)