3 papers
cs.LG2025
Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs
Ishan Khurjekar, Indrashish Saha, Lori Graham-Brady +1
Systems governed by partial differential equations (PDEs) require computationally intensive numerical solvers to predict spatiotemporal field evolution. While machine learning (ML)…
cond-mat.mtrl-sci2025
Numerical and data-driven modeling of spall failure in polycrystalline ductile materials
Indrashish Saha, Lori Graham-Brady
Developing materials with tailored mechanical performance requires iteration over a large number of proposed designs. When considering dynamic fracture, experiments at every iterat…
cs.LG2025
Physics-Informed Latent Neural Operator for Real-time Predictions of time-dependent parametric PDEs
Sharmila Karumuri, Lori Graham-Brady, Somdatta Goswami
Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between…