mlsanityData to 7 Oct 2026

Phase Retrieval using Single-Instance Deep Generative Prior

arXiv 2106.04812 ↗First posted 9 Jun 2021cs.LG eess.IVcited by 4

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Abstract (arXiv)

Several deep learning methods for phase retrieval exist, but most of them fail on realistic data without precise support information. We propose a novel method based on single-instance deep generative prior that works well on complex-valued crystal data.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 9 Jun 2021.

Builds on

6 of 14 references.

References · 6

  1. 2017Deep Image Priorcited by 1,097
  2. 2020Deep Learning Techniques for Inverse Problems in Imagingcited by 290
  3. 2018Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networkscited by 120
  4. 2019Algorithmic Guarantees for Inverse Imaging with Untrained Network Priorscited by 32
  5. 2020Deep Phase Decoder: Self-calibrating phase microscopy with an untrained deep neural networkcited by 24
  6. 2020Phase Retrieval with Holography and Untrained Priors: Tackling the Challenges of Low-Photon Nanoscale Imagingcited by 6

Built on by

Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 1.

4 papers.

  1. 2021Early Stopping for Deep Image Priorcited by 44
  2. 2022Blind Image Deblurring with Unknown Kernel Size and Substantial Noisecited by 10
  3. 2022Practical Phase Retrieval Using Double Deep Image Priorscited by 10
  4. 2024Low-light phase retrieval with implicit generative priorscited by 1