Vinayak Killedar — accepted AI-conference papers

2022

Compressive Phase Retrieval Based On Sparse Latent Generative Priors

Vinayak Killedar, Chandra Sekhar Seelamantula

ICASSP 2022accepted

We address the problem of compressive phase retrieval (CPR) based on generative prior. The problem is ill-posed and requires structural assumptions. CPR techniques impose sparsity prior on the signal to perform reconstruction from compressive phaseless measurements. Recent developments in data-drive…

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2021

Sparsity Driven Latent Space Sampling for Generative Prior Based Compressive Sensing

Vinayak Killedar, Praveen Kumar Pokala, Chandra Sekhar Seelamantula

ICASSP 2021accepted

We address the problem of recovering signals from compressed measurements based on generative priors. Recently, generative-model based compressive sensing (GMCS) methods have shown superior performance over traditional compressive sensing (CS) techniques in recovering signals from fewer measurements…

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