42 citations · 88 across the 15 of their papers we have counts for
4 papers · 1 filter
Compositional Generation for Long-Horizon Coupled PDEs
Somayajulu L. N. Dhulipala, Deep Ray, Nicholas Forman
Simulating coupled PDE systems is computationally intensive, and prior efforts have largely focused on training surrogates on the joint (coupled) data, which requires a large amoun…
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks
Denny Thaler, Somayajulu L. N. Dhulipala, Franz Bamer +2
We present a new Subset Simulation approach using Hamiltonian neural network-based Monte Carlo sampling for reliability analysis. The proposed strategy combines the superior sampli…
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference
Somayajulu L. N. Dhulipala, Yifeng Che, Michael D. Shields
Although the no-u-turn sampler (NUTS) is a widely adopted method for performing Bayesian inference, it requires numerous posterior gradients which can be expensive to compute in pr…
Active Learning with Multifidelity Modeling for Efficient Rare Event Simulation
S. L. N. Dhulipala, M. D. Shields, B. W. Spencer +4
While multifidelity modeling provides a cost-effective way to conduct uncertainty quantification with computationally expensive models, much greater efficiency can be achieved by a…