11 citations · 11 across the 4 of their papers we have counts for
4 papers
PINNsur: Physics-Informed Neural Networks for PDEs on Curved Surfaces
Pranav Jain, Navami Kairanda, Peter Yichen Chen +1
Partial differential equations (PDEs) on surfaces are fundamental to scientific computing and geometry processing. A popular approach to solving PDEs on surfaces is the finite elem…
Stratified adaptive sampling for derivative-free stochastic trust-region optimization
Giovanni Amici, Sara Shashaani, Pranav Jain
There is emerging evidence that trust-region (TR) algorithms are very effective at solving derivative-free nonconvex stochastic optimization problems in which the objective functio…
Simulation Model Calibration with Dynamic Stratification and Adaptive Sampling
Pranav Jain, Sara Shashaani, Eunshin Byon
Calibrating simulation models that take large quantities of multi-dimensional data as input is a hard simulation optimization problem. Existing adaptive sampling strategies offer a…
High-Order Incremental Potential Contact for Elastodynamic Simulation on Curved Meshes
Zachary Ferguson, Pranav Jain, Denis Zorin +2
High-order bases provide major advantages over linear ones in terms of efficiency, as they provide (for the same physical model) higher accuracy for the same running time, and reli…