198 citations
- Brown UniversityUS12 papers
- Brownsville Public LibraryUS4 papers
- McGill UniversityCA2 papers
- Princeton UniversityUS2 papers
- University of PennsylvaniaUS2 papers
- University of Science and Technology of ChinaCN2 papers
- Alere (United Kingdom)GB1 paper
- Astro Space CenterRU1 paper
- Bauhaus-Universität WeimarDE1 paper
- Boston UniversityUS1 paper
- Central South UniversityCN1 paper
- Chalmers University of TechnologySE1 paper
37 papers
Learning Nonlinear Responses in PET Bottle Buckling with a Hybrid DeepONet-Transolver Framework
Varun Kumar, Jing Bi, Cyril Ngo Ngoc +2
Neural surrogates and operator networks for solving partial differential equation (PDE) problems have attracted significant research interest in recent years. However, most existin…
Forms of Nice Functions
Anthony G. O'Farrell
You can invent striking and challenging problems with unique solution by building some symmetry into functional equations. Some are suitable for high school; others could generate…
A Digital Twin for Diesel Engines: Operator-infused Physics-Informed Neural Networks with Transfer Learning for Engine Health Monitoring
Kamaljyoti Nath, Varun Kumar, Daniel J. Smith +1
Improving diesel engine efficiency, reducing emissions, and enabling robust health monitoring have been critical research topics in engine modelling. While recent advancements in t…
Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization
Tobias Duswald, Brendan Keith, Boyan Lazarov +2
This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on applications in computational m…
A high-order local discontinuous Galerkin method for the -Laplace equation
Yue Wu, Yan Xu
We study the high-order local discontinuous Galerkin (LDG) method for the -Laplace equation. We reformulate our spatial discretization as an equivalent convex minimization probl…
Randomness of Shapes and Statistical Inference on Shapes via the Smooth Euler Characteristic Transform
Kun Meng, Jinyu Wang, Lorin Crawford +1
In this article, we establish the mathematical foundations for modeling the randomness of shapes and conducting statistical inference on shapes using the smooth Euler characteristi…