169 citations · 837 across the 31 of their papers we have counts for
31 papers
Simulation of Stochastic Non-Equilibrium Thermal Effects of Particle Inclusions within Fluid Interfaces and Membranes
Dev Jasuja, Paul J. Atzberger
We formulate theoretical modeling approaches and develop practical computational simulation methods for investigating the non-equilibrium statistical mechanics of fluid interfaces…
Geometric Neural Operators (GNPs) for Data-Driven Deep Learning of Non-Euclidean Operators
Blaine Quackenbush, Paul J. Atzberger
We introduce Geometric Neural Operators (GNPs) for accounting for geometric contributions in data-driven deep learning of operators. We show how GNPs can be used (i) to estimate ge…
SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics
Panos Stinis, Constantinos Daskalakis, Paul J. Atzberger
We introduce adversarial learning methods for data-driven generative modeling of the dynamics of -order stochastic systems. Our approach builds on Generative Adversarial Ne…
Incorporating Shear into Stochastic Eulerian Lagrangian Methods for Rheological Studies of Complex Fluids and Soft Materials
Paul J. Atzberger
We develop computational methods that incorporate shear into fluctuating hydrodynamics methods. We are motivated by the rheological responses of complex fluids and soft materials.…
Magnus Exponential Integrators for Stiff Time-Varying Stochastic Systems
Dev Jasuja, P. J. Atzberger
We introduce exponential numerical integration methods for stiff stochastic dynamical systems of the form …
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions
Ryan Lopez, Paul J. Atzberger
We develop data-driven methods incorporating geometric and topological information to learn parsimonious representations of nonlinear dynamics from observations. The approaches lea…