no code implementations • ICLR 2022 • Juncheng Dong, Simiao Ren, Yang Deng, Omar Khatib, Jordan Malof, Mohammadreza Soltani, Willie Padilla, Vahid Tarokh
To this end, we propose a physics-infused deep neural network based on the Blaschke products for phase retrieval.
1 code implementation • NeurIPS 2021 • Yang Deng*, Juncheng Dong*, Simiao Ren*, Omar Khatib, Mohammadreza Soltani, Vahid Tarokh, Willie Padilla, Jordan Malof
Recently, it has been shown that deep learning can be an alternative solution to infer the relationship between an AEM geometry and its properties using a (relatively) small pool of CEMS data.
1 code implementation • NeurIPS 2020 • Simiao Ren, Willie Padilla, Jordan Malof
We consider the task of solving generic inverse problems, where one wishes to determine the hidden parameters of a natural system that will give rise to a particular set of measurements.