Nathaniel Trask

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 48

Top Topics

Diffusion Equation

Reproducing Kernel

Unstructured Data

Top Venues

J. Comput. Phys.

AAAI Spring Symposium: MLPS

SIAM J. Sci. Comput.

Publications

Jonas A. Actor, Xiaozhe Hu, Andy Huang, Scott A. Roberts, Nathaniel Trask
Data-driven Whitney forms for structure-preserving control volume analysis. J. Comput. Phys. 496 (2024)
Bradley H. Theilman, Qian Zhang, Adar Kahana, Eric C. Cyr, Nathaniel Trask, James B. Aimone, George Em Karniadakis
Spiking Physics-Informed Neural Networks on Loihi 2. NICE (2024)
Shuai Jiang, Jonas A. Actor, Scott A. Roberts, Nathaniel Trask
A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling. CoRR (2024)
Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask
Efficiently Parameterized Neural Metriplectic Systems. CoRR (2024)
Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park
Graph Convolutions Enrich the Self-Attention in Transformers! CoRR (2023)
James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang, Nathaniel Trask
A Stable Mimetic Finite-Difference Method for Convection-Dominated Diffusion Equations. SIAM J. Sci. Comput. 45 (6) (2023)
Elise Walker, Jonas A. Actor, Carianne Martinez, Nathaniel Trask
Causal disentanglement of multimodal data. CoRR (2023)
Anthony Gruber, Kookjin Lee, Nathaniel Trask
Reversible and irreversible bracket-based dynamics for deep graph neural networks. NeurIPS (2023)
James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang, Nathaniel Trask
A Stable Mimetic Finite-Difference Method for Convection-Dominated Diffusion Equations. SIAM J. Sci. Comput. 45 (3) (2023)
Anthony Gruber, Kookjin Lee, Nathaniel Trask
Reversible and irreversible bracket-based dynamics for deep graph neural networks. CoRR (2023)
Tiffany Fan, Nathaniel Trask, Marta D'Elia, Eric Darve
Probabilistic partition of unity networks for high-dimensional regression problems. CoRR (2022)
Kookjin Lee, Nathaniel Trask
Parameter-varying neural ordinary differential equations with partition-of-unity networks. CoRR (2022)
Jonas A. Actor, Andy Huang, Nathaniel Trask
Polynomial-Spline Networks with Exact Integrals and Convergence Rates. SSCI (2022)
Khemraj Shukla, Mengjia Xu, Nathaniel Trask, George Em Karniadakis
Scalable algorithms for physics-informed neural and graph networks. CoRR (2022)
Marco Pasetto, Zhaoxiang Shen, Marta D'Elia, Xiaochuan Tian, Nathaniel Trask, David Kamensky
Efficient optimization-based quadrature for variational discretization of nonlocal problems. CoRR (2022)
Nathaniel Trask, Carianne Martinez, Kookjin Lee, Brad Boyce
Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery. CoRR (2022)
James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang, Nathaniel Trask
A Stable Mimetic Finite-Difference Method for Convection-Dominated Diffusion Equations. CoRR (2022)
Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric C. Cyr
Hierarchical partition of unity networks: fast multilevel training. MSML (2022)
Nathaniel Trask, Andy Huang, Xiaozhe Hu
Enforcing exact physics in scientific machine learning: A data-driven exterior calculus on graphs. J. Comput. Phys. 456 (2022)
Kookjin Lee, Nathaniel Trask, Panos Stinis
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling. MSML (2022)
Jonas A. Actor, Andy Huang, Nathaniel Trask
Polynomial-Spline Neural Networks with Exact Integrals. CoRR (2021)
Nathaniel Trask, Mamikon A. Gulian, Andy Huang, Kookjin Lee
Probabilistic partition of unity networks: clustering based deep approximation. CoRR (2021)
Yu Leng, Xiaochuan Tian, Nathaniel Trask, John T. Foster
Asymptotically Compatible Reproducing Kernel Collocation and Meshfree Integration for Nonlocal Diffusion. SIAM J. Numer. Anal. 59 (1) (2021)
Ravi G. Patel, Nathaniel Trask, Mamikon A. Gulian, Eric C. Cyr
A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity. AAAI Spring Symposium: MLPS (2021)
Masoud Behzadinasab, Georgios Moutsanidis, Nathaniel Trask, John T. Foster, Yuri Bazilevs
Coupling of IGA and Peridynamics for Air-Blast Fluid-Structure Interaction Using an Immersed Approach. CoRR (2021)
Yue Yu, Huaiqian You, Nathaniel Trask
An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture. CoRR (2021)
Masoud Behzadinasab, Mert Alaydin, Nathaniel Trask, Yuri Bazilevs
A General-Purpose, Inelastic, Rotation-Free Kirchhoff-Love Shell Formulation for Peridynamics. CoRR (2021)
Kookjin Lee, Nathaniel Trask, Panos Stinis
Machine learning structure preserving brackets for forecasting irreversible processes. NeurIPS (2021)
Kookjin Lee, Nathaniel Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr
Partition of Unity Networks: Deep HP-Approximation. AAAI Spring Symposium: MLPS (2021)
Xinhui Wu, Nathaniel Trask, Jesse Chan
Entropy stable discontinuous Galerkin methods for the shallow water equations with subcell positivity preservation. CoRR (2021)
Andy Huang, Nathaniel Trask, Christopher Brissette, Xiaozhe Hu
Greedy Fiedler Spectral Partitioning for Data-driven Discrete Exterior Calculus. AAAI Spring Symposium: MLPS (2021)
Kookjin Lee, Nathaniel Trask, Panos Stinis
Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling. 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)
Masoud Behzadinasab, Nathaniel Trask, Yuri Bazilevs
A unified, stable and accurate meshfree framework for peridynamic correspondence modeling. Part I: core methods. CoRR (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)
Nathaniel Trask, Andy Huang, Xiaozhe Hu
Enforcing exact physics in scientific machine learning: a data-driven exterior calculus on graphs. CoRR (2020)
Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon A. Gulian, Marta D'Elia
Data-driven learning of robust nonlocal physics from high-fidelity synthetic data. CoRR (2020)
Nathaniel Trask, Pavel B. Bochev, Mauro Perego
A conservative, consistent, and scalable meshfree mimetic method. J. Comput. Phys. 409 (2020)
Nathaniel Trask, Benjamin Huntington, David J. Littlewood
Asymptotically compatible meshfree discretization of state-based peridynamics for linearly elastic composite materials. CoRR (2019)
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)
Huaiqian You, Xin Yang Lu, Nathaniel Trask, Yue Yu
An Asymptotically Compatible Approach For Neumann-Type Boundary Condition On Nonlocal Problems. CoRR (2019)
Nathaniel Trask, Pavel B. Bochev, Mauro Perego
Mitigation of the self-force effect in unstructured PIC codes using generalized moving least squares. Comput. Math. Appl. 78 (2) (2019)
Pavel B. Bochev, Nathaniel Trask, Paul Kuberry, Mauro Perego
Mesh-Hardened Finite Element Analysis Through a Generalized Moving Least-Squares Approximation of Variational Problems. LSSC (2019)
Yu Leng, Xiaochuan Tian, Nathaniel Trask, John T. Foster
Asymptotically compatible reproducing kernel collocation and meshfree integration for nonlocal diffusion. CoRR (2019)
Nathaniel Trask, Martin R. Maxey, Xiaozhe Hu
A compatible high-order meshless method for the Stokes equations with applications to suspension flows. J. Comput. Phys. 355 (2018)
Nathaniel Trask, Mauro Perego, Pavel B. Bochev
A High-Order Staggered Meshless Method for Elliptic Problems. SIAM J. Sci. Comput. 39 (2) (2017)
Nathaniel Trask, Martin R. Maxey, Xiaozhe Hu
Compact moving least squares: An optimization framework for generating high-order compact meshless discretizations. J. Comput. Phys. 326 (2016)