43 citations · 65 across the 3 of their papers we have counts for
4 papers
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures
Jarom D. Hogue, Robert M. Kirby, Akil Narayan
Deep learning using neural networks is an effective technique for generating models of complex data. However, training such models can be expensive when networks have large model c…
A fast methodology for large-scale focusing inversion of gravity and magnetic data using the structured model matrix and the fast Fourier transform
Rosemary A. Renaut, Jarom D. Hogue, Saeed Vatankhah
Focusing inversion of potential field data for the recovery of sparse subsurface structures from surface measurement data on a uniform grid is discussed. For the uniform grid the m…
Generalized L-norm joint inversion of gravity and magnetic data using cross-gradient constraint
Saeed Vatankhah, Shuang Liu, Rosemary A. Renaut +2
A generalized unifying approach for -norm joint inversion of gravity and magnetic data using the cross-gradient constraint is presented. The presented framework incorporates…
A Tutorial and Open Source Software for the Efficient Evaluation of Gravity and Magnetic Kernels
Jarom D Hogue, Rosemary A Renaut, Saeed Vatankhah
Fast computation of three-dimensional gravity and magnetic forward models is considered. Measurement data is assumed to be obtained on a uniform grid which is staggered with respec…