10 citations · 11 across the 2 of their papers we have counts for
5 papers
Automated and Accurate Geometry Extraction and Shape Optimization of 3D Topology Optimization Results
Marco K. Swierstra, Deepak K. Gupta, Matthijs Langelaar
Designs generated by density-based topology optimization (TO) exhibit jagged and/or smeared boundaries, which forms an obstacle to their integration with existing CAD tools. Addres…
Stacked autoencoders based machine learning for noise reduction and signal reconstruction in geophysical data
Debjani Bhowick, Deepak K. Gupta, Saumen Maiti +1
Autoencoders are neural network formulations where the input and output of the network are identical and the goal is to identify the hidden representation in the provided datasets.…
Design and analysis adaptivity in multi-resolution topology optimization
Deepak K. Gupta, Fred van Keulen, Matthijs Langelaar
Multiresolution topology optimization (MTO) methods involve decoupling of the design and analysis discretizations, such that a high-resolution design can be obtained at relatively…
Deep Autoassociative Neural Networks for Noise Reduction in Seismic data
Debjani Bhowmick, Deepak K. Gupta, Saumen Maiti +1
Machine learning is currently a trending topic in various science and engineering disciplines, and the field of geophysics is no exception. With the advent of powerful computers, i…
Velocity-Porosity Supermodel: A Deep Neural Networks based concept
Debjani Bhowmick, Deepak K. Gupta, Saumen Maiti +1
Rock physics models (RPMs) are used to estimate the elastic properties (e.g. velocity, moduli) from the rock properties (e.g. porosity, lithology, fluid saturation). However, the r…