Invertibility of convolutional generative networks from partial measurements

The problem of inverting generative neural networks (i.e., to recover the input latent code given partial network output), motivated by image inpainting, has recently been studied by a prior work that focused on fully-connected networks. In this work, we present new theoretical results on convolutio...

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Bibliografski detalji
Glavni autori: Ma, Fangchang, Ayaz, Ulas, Karaman, Sertac
Daljnji autori: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Članak
Jezik:English
Izdano: Neural Information Processing Systems Foundation, Inc. 2020
Online pristup:https://hdl.handle.net/1721.1/125238