Pinned Repositories
Bio-inspired-low-porosity-structures-using-Neural-Networks-GRU-Implemenation
The GRU model, trained to predict stress-strain response and energy absorption, uses eight discrete parameters to characterize the design space. It efficiently predicts new design responses in 0.16 milliseconds, enabling the rapid performance evaluation of 128,000 designs any given strain rate and final strain.
CMDS-14-impact-resistantance-NN-prediction-
Neural Networks to Explore Structure-Property Relations in Bio-Inspired Impact-Resistant Structures
coursera-gan-specialization
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
dem_hyperelasticity
A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on the idea of minimum potential energy. The method is named "Deep Energy Method".
GLOnet
Global optimization based on generative neural networks
scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
Voronoi3D
SciPy library main repository
shashankk42's Repositories
shashankk42/coursera-gan-specialization
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
shashankk42/dem_hyperelasticity
A method based on a feed forward neural network to solve partial differential equations in nonlinear elasticity at finite strain based on the idea of minimum potential energy. The method is named "Deep Energy Method".
shashankk42/GLOnet
Global optimization based on generative neural networks
shashankk42/scientific-visualization-book
An open access book on scientific visualization using python and matplotlib
shashankk42/Voronoi3D
SciPy library main repository