Paul J. Atzberger

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 23

Top Topics

Nonlinear Dynamics

Curved Surfaces

Machine Learning Methods

Top Venues

J. Comput. Phys.

AAAI Spring Symposium: MLPS

SIAM J. Sci. Comput.

Publications

Blaine Quackenbush, Paul J. Atzberger
Geometric Neural Operators (GNPs) for Data-Driven Deep Learning of Non-Euclidean Operators. CoRR (2024)
Panos Stinis, Constantinos Daskalakis, Paul J. Atzberger
SDYN-GANs: Adversarial Learning Methods for Multistep Generative Models for General Order Stochastic Dynamics. CoRR (2023)
David A. Rower, Paul J. Atzberger
Coarse-grained methods for heterogeneous vesicles with phase-separated domains: Elastic mechanics of shape fluctuations, plate compression, and channel insertion. Math. Comput. Simul. 209 (2023)
Paul J. Atzberger
MLMOD: Machine Learning Methods for Data-Driven Modeling in LAMMPS. J. Open Source Softw. 8 (90) (2023)
Paul J. Atzberger
Incorporating Shear into Stochastic Eulerian Lagrangian Methods for Rheological Studies of Complex Fluids and Soft Materials. CoRR (2022)
David Rower, Misha Padidar, Paul J. Atzberger
Surface fluctuating hydrodynamics methods for the drift-diffusion dynamics of particles and microstructures within curved fluid interfaces. J. Comput. Phys. 455 (2022)
Ben J. Gross, Paul Kuberry, Paul J. Atzberger
First-passage time statistics on surfaces of general shape: Surface PDE solvers using Generalized Moving Least Squares (GMLS). J. Comput. Phys. 453 (2022)
Ryan Lopez, Paul J. Atzberger
GD-VAEs: Geometric Dynamic Variational Autoencoders for Learning Nonlinear Dynamics and Dimension Reductions. CoRR (2022)
Dev Jasuja, Paul J. Atzberger
Magnus Exponential Integrators for Stiff Time-Varying Stochastic Systems. CoRR (2022)
Ryan Lopez, Paul J. Atzberger
Variational Autoencoders for Learning Nonlinear Dynamics of PDEs and Reductions. AAAI Spring Symposium: MLPS (2021)
Paul J. Atzberger
MLMOD Package: Machine Learning Methods for Data-Driven Modeling in LAMMPS. CoRR (2021)
Patrick D. Tran, Thomas A. Blanpied, Paul J. Atzberger
Drift-Diffusion Dynamics and Phase Separation in Curved Cell Membranes and Dendritic Spines: Hybrid Discrete-Continuum Methods. CoRR (2021)
Ben J. Gross, Paul Kuberry, Paul J. Atzberger
First-Passage Time Statistics on Surfaces of General Shape: Surface PDE Solvers using Generalized Moving Least Squares (GMLS). CoRR (2021)
Ben J. Gross, Nathaniel Trask, Paul Kuberry, Paul J. Atzberger
Meshfree methods on manifolds for hydrodynamic flows on curved surfaces: A Generalized Moving Least-Squares (GMLS) approach. J. Comput. Phys. 409 (2020)
Nathaniel Trask, Ravi G. Patel, Paul J. Atzberger, Ben J. Gross
GMLS-Nets: A Machine Learning Framework for Unstructured Data. AAAI Spring Symposium: MLPS (2020)
Ryan Lopez, Paul J. Atzberger
Variational Autoencoders for Learning Nonlinear Dynamics of Physical Systems. CoRR (2020)
Nathaniel Trask, Ravi G. Patel, Ben J. Gross, Paul J. Atzberger
GMLS-Nets: A framework for learning from unstructured data. CoRR (2019)
Ben J. Gross, Nathaniel Trask, Paul Kuberry, Paul J. Atzberger
Meshfree Methods on Manifolds for Hydrodynamic Flows on Curved Surfaces: A Generalized Moving Least-Squares (GMLS) Approach. CoRR (2019)
David Rower, Misha Padidar, Paul J. Atzberger
Surface Fluctuating Hydrodynamics Methods for the Drift-Diffusion Dynamics of Particles and Microstructures within Curved Fluid Interfaces. CoRR (2019)
Ben J. Gross, Paul J. Atzberger
Spectral Numerical Exterior Calculus Methods for Differential Equations on Radial Manifolds. J. Sci. Comput. 76 (1) (2018)
Ben J. Gross, Paul J. Atzberger
Hydrodynamic flows on curved surfaces: Spectral numerical methods for radial manifold shapes. J. Comput. Phys. 371 (2018)
Paul J. Atzberger
Importance of the Mathematical Foundations of Machine Learning Methods for Scientific and Engineering Applications. CoRR (2018)
Y. Wang, Jon Karl Sigurdsson, Paul J. Atzberger
Fluctuating Hydrodynamics Methods for Dynamic Coarse-Grained Implicit-Solvent Simulations in LAMMPS. SIAM J. Sci. Comput. 38 (5) (2016)
Gil Tabak, Paul J. Atzberger
Stochastic Reductions for Inertial Fluid-Structure Interactions Subject to Thermal Fluctuations. SIAM J. Appl. Math. 75 (4) (2015)
Chen-Hung Wu, Thomas G. Fai, Paul J. Atzberger, Charles S. Peskin
Simulation of Osmotic Swelling by the Stochastic Immersed Boundary Method. SIAM J. Sci. Comput. 37 (4) (2015)
Pat Plunkett, Jonathan J. Hu, Christopher M. Siefert, Paul J. Atzberger
Spatially adaptive stochastic methods for fluid-structure interactions subject to thermal fluctuations in domains with complex geometries. J. Comput. Phys. 277 (2014)
Ava J. Mauro, Jon Karl Sigurdsson, Justin Shrake, Paul J. Atzberger, Samuel A. Isaacson
A First-Passage Kinetic Monte Carlo method for reaction-drift-diffusion processes. J. Comput. Phys. 259 (2014)
Jon Karl Sigurdsson, Frank L. H. Brown, Paul J. Atzberger
Hybrid continuum-particle method for fluctuating lipid bilayer membranes with diffusing protein inclusions. J. Comput. Phys. 252 (2013)
Paul J. Atzberger
Stochastic Eulerian Lagrangian methods for fluid-structure interactions with thermal fluctuations. J. Comput. Phys. 230 (8) (2011)
Paul J. Atzberger
Spatially adaptive stochastic numerical methods for intrinsic fluctuations in reaction-diffusion systems. J. Comput. Phys. 229 (9) (2010)
Paul J. Atzberger, Peter R. Kramer
Error analysis of a stochastic immersed boundary method incorporating thermal fluctuations. Math. Comput. Simul. 79 (3) (2008)
Paul J. Atzberger, Peter R. Kramer, Charles S. Peskin
A stochastic immersed boundary method for fluid-structure dynamics at microscopic length scales. J. Comput. Phys. 224 (2) (2007)