5 citations · 7 across the 6 of their papers we have counts for
4 papers · 1 filter
Learning Generative Prior with Latent Space Sparsity Constraints
Vinayak Killedar, Praveen Kumar Pokala, Chandra Sekhar Seelamantula
We address the problem of compressed sensing using a deep generative prior model and consider both linear and learned nonlinear sensing mechanisms, where the nonlinear one involves…
Quantized Proximal Averaging Network for Analysis Sparse Coding
Kartheek Kumar Reddy Nareddy, Mani Madhoolika Bulusu, Praveen Kumar Pokala +1
We solve the analysis sparse coding problem considering a combination of convex and non-convex sparsity promoting penalties. The multi-penalty formulation results in an iterative a…
NuSPAN: A Proximal Average Network for Nonuniform Sparse Model -- Application to Seismic Reflectivity Inversion
Swapnil Mache, Praveen Kumar Pokala, Kusala Rajendran +1
We solve the problem of sparse signal deconvolution in the context of seismic reflectivity inversion, which pertains to high-resolution recovery of the subsurface reflection coeffi…
DuRIN: A Deep-unfolded Sparse Seismic Reflectivity Inversion Network
Swapnil Mache, Praveen Kumar Pokala, Kusala Rajendran +1
We consider the reflection seismology problem of recovering the locations of interfaces and the amplitudes of reflection coefficients from seismic data, which are vital for estimat…