Efficient training of physics-informed neural networks via importance sampling. - Mohammad Amin Nabian; Rini Jasmine Gladstone; Hadi Meidani (Comput. Aided Civ. Infrastructure Eng., 2021)

Robust Topology Optimization Using Variational Autoencoders. - Rini Jasmine Gladstone; Mohammad Amin Nabian; Vahid Keshavarzzadeh; Hadi Meidani (CoRR, 2021)

FO-PINNs: A First-Order formulation for Physics Informed Neural Networks. - Rini Jasmine Gladstone; Mohammad Amin Nabian; Hadi Meidani (CoRR, 2022)

GNN-based physics solver for time-independent PDEs. - Rini Jasmine Gladstone; Helia Rahmani; Vishvas Suryakumar; Hadi Meidani; Marta D'Elia; Ahmad Zareei (CoRR, 2023)

A Multi-Fidelity Graph U-Net Model for Accelerated Physics Simulations. - Rini Jasmine Gladstone; Hadi Meidani (CoRR, 2024)

PINN-FEM: A Hybrid Approach for Enforcing Dirichlet Boundary Conditions in Physics-Informed Neural Networks. - Nahil Sobh; Rini Jasmine Gladstone; Hadi Meidani (CoRR, 2025)