no code implementations • 12 Sep 2023 • Shaik Basheeruddin Shah, Pradyumna Pradhan, Wei Pu, Ramunaidu Randhi, Miguel R. D. Rodrigues, Yonina C. Eldar
Hence, we provide conditions, in terms of the network width and the number of training samples, on these unfolded networks for the PL$^*$ condition to hold.
no code implementations • 23 Jan 2022 • Wei Pu, Jun-Jie Huang, Barak Sober, Nathan Daly, Catherine Higgitt, Ingrid Daubechies, Pier Luigi Dragotti, Miguel Rodigues
In this paper, we focus on X-ray images of paintings with concealed sub-surface designs (e. g., deriving from reuse of the painting support or revision of a composition by the artist), which include contributions from both the surface painting and the concealed features.
no code implementations • 20 Oct 2021 • Wei Pu, Chao Zhou, Yonina C. Eldar, Miguel R. D. Rodrigues
In this paper, we consider deep neural networks for solving inverse problems that are robust to forward model mis-specifications.
1 code implementation • 25 May 2021 • Divam Gupta, Wei Pu, Trenton Tabor, Jeff Schneider
Instead, the learning of a good internal bird's eye view feature representation is effective for layout estimation.
no code implementations • 16 Sep 2020 • Wei Pu, Barak Sober, Nathan Daly, Zahra Sabetsarvestani, Catherine Higgitt, Ingrid Daubechies, Miguel R. D. Rodrigues
These features are then used to (1) reproduce both of the original RGB images, (2) reconstruct the hypothetical separated X-ray images, and (3) regenerate the mixed X-ray image.