Nathaniel Trask

58 papers A* 4Journal 45Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs. SIAM J. Sci. Comput. Adrienne M. Propp, Jonas A. Actor, Elise Walker, Houman Owhadi, Nathaniel Trask, Daniel M. Tartakovsky
2026	J	`jnl`	Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs. CoRR Benjamin D. Shaffer, Shawn Koohy, Brooks Kinch, M. Ani Hsieh, Nathaniel Trask
2025	J	`jnl`	A discontinuous piecewise polynomial generalized moving least squares scheme for robust finite element analysis on arbitrary grids. Eng. Comput. Paul Kuberry, Pavel B. Bochev, Jacob Koester, Nathaniel Trask
2025	J	`jnl`	Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems. CoRR Quercus Hernandez, Max Win, Thomas C. O'Connor, Paulo E. Arratia, Nathaniel Trask
2025	J	`jnl`	Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs. CoRR Adrienne M. Propp, Jonas A. Actor, Elise Walker, Houman Owhadi, Nathaniel Trask, Daniel M. Tartakovsky
2025	A*	`conf`	Efficiently Parameterized Neural Metriplectic Systems. ICLR Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask
2025	J	`jnl`	Multi-robot Multi-source Localization in Complex Flows with Physics-Preserving Environment Models. CoRR Benjamin D. Shaffer, Victoria Edwards, Brooks Kinch, Nathaniel Trask, M. Ani Hsieh
2025	J	`jnl`	Physics-informed sensor coverage through structure preserving machine learning. CoRR Benjamin D. Shaffer, Brooks Kinch, Joseph Klobusicky, M. Ani Hsieh, Nathaniel Trask
2025	J	`jnl`	Structure-Preserving Digital Twins via Conditional Neural Whitney Forms. CoRR Brooks Kinch, Benjamin D. Shaffer, Elizabeth Armstrong, Michael Meehan, John Hewson, Nathaniel Trask
2024	J	`jnl`	A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling. CoRR Shuai Jiang, Jonas A. Actor, Scott A. Roberts, Nathaniel Trask
2024	J	`jnl`	Data-driven Whitney forms for structure-preserving control volume analysis. J. Comput. Phys. Jonas A. Actor, Xiaozhe Hu, Andy Huang, Scott A. Roberts, Nathaniel Trask
2024	J	`jnl`	Efficiently Parameterized Neural Metriplectic Systems. CoRR Anthony Gruber, Kookjin Lee, Haksoo Lim, Noseong Park, Nathaniel Trask
2024	J	`jnl`	Gaussian Variational Schemes on Bounded and Unbounded Domains. CoRR Jonas A. Actor, Anthony Gruber, Eric C. Cyr, Nathaniel Trask
2024	A*	`conf`	Graph Convolutions Enrich the Self-Attention in Transformers! NeurIPS Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park
2024	—	`conf`	Spiking Physics-Informed Neural Networks on Loihi 2. NICE Bradley H. Theilman, Qian Zhang, Adar Kahana, Eric C. Cyr, Nathaniel Trask, James B. Aimone, George Em Karniadakis
2023	J	`jnl`	A Stable Mimetic Finite-Difference Method for Convection-Dominated Diffusion Equations. SIAM J. Sci. Comput. James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang, Nathaniel Trask
2023	J	`jnl`	Causal disentanglement of multimodal data. CoRR Elise Walker, Jonas A. Actor, Carianne Martinez, Nathaniel Trask
2023	J	`jnl`	Graph Convolutions Enrich the Self-Attention in Transformers! CoRR Jeongwhan Choi, Hyowon Wi, Jayoung Kim, Yehjin Shin, Kookjin Lee, Nathaniel Trask, Noseong Park
2023	A*	`conf`	Reversible and irreversible bracket-based dynamics for deep graph neural networks. NeurIPS Anthony Gruber, Kookjin Lee, Nathaniel Trask
2023	J	`jnl`	Reversible and irreversible bracket-based dynamics for deep graph neural networks. CoRR Anthony Gruber, Kookjin Lee, Nathaniel Trask
2022	J	`jnl`	A Stable Mimetic Finite-Difference Method for Convection-Dominated Diffusion Equations. CoRR James H. Adler, Casey Cavanaugh, Xiaozhe Hu, Andy Huang, Nathaniel Trask
2022	J	`jnl`	Efficient optimization-based quadrature for variational discretization of nonlocal problems. CoRR Marco Pasetto, Zhaoxiang Shen, Marta D'Elia, Xiaochuan Tian, Nathaniel Trask, David Kamensky
2022	J	`jnl`	Enforcing exact physics in scientific machine learning: A data-driven exterior calculus on graphs. J. Comput. Phys. Nathaniel Trask, Andy Huang, Xiaozhe Hu
2022	—	`conf`	Hierarchical partition of unity networks: fast multilevel training. MSML Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric C. Cyr
2022	J	`jnl`	Parameter-varying neural ordinary differential equations with partition-of-unity networks. CoRR Kookjin Lee, Nathaniel Trask
2022	—	`conf`	Polynomial-Spline Networks with Exact Integrals and Convergence Rates. SSCI Jonas A. Actor, Andy Huang, Nathaniel Trask
2022	J	`jnl`	Probabilistic partition of unity networks for high-dimensional regression problems. CoRR Tiffany Fan, Nathaniel Trask, Marta D'Elia, Eric Darve
2022	J	`jnl`	Scalable algorithms for physics-informed neural and graph networks. CoRR Khemraj Shukla, Mengjia Xu, Nathaniel Trask, George Em Karniadakis
2022	—	`conf`	Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling. MSML Kookjin Lee, Nathaniel Trask, Panos Stinis
2022	J	`jnl`	Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery. CoRR Nathaniel Trask, Carianne Martinez, Kookjin Lee, Brad Boyce
2021	—	`conf`	A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity. AAAI Spring Symposium: MLPS Ravi G. Patel, Nathaniel Trask, Mamikon A. Gulian, Eric C. Cyr
2021	J	`jnl`	A General-Purpose, Inelastic, Rotation-Free Kirchhoff-Love Shell Formulation for Peridynamics. CoRR Masoud Behzadinasab, Mert Alaydin, Nathaniel Trask, Yuri Bazilevs
2021	J	`jnl`	An asymptotically compatible treatment of traction loading in linearly elastic peridynamic fracture. CoRR Yue Yu, Huaiqian You, Nathaniel Trask
2021	J	`jnl`	Asymptotically Compatible Reproducing Kernel Collocation and Meshfree Integration for Nonlocal Diffusion. SIAM J. Numer. Anal. Yu Leng, Xiaochuan Tian, Nathaniel Trask, John T. Foster
2021	J	`jnl`	Coupling of IGA and Peridynamics for Air-Blast Fluid-Structure Interaction Using an Immersed Approach. CoRR Masoud Behzadinasab, Georgios Moutsanidis, Nathaniel Trask, John T. Foster, Yuri Bazilevs
2021	J	`jnl`	Entropy stable discontinuous Galerkin methods for the shallow water equations with subcell positivity preservation. CoRR Xinhui Wu, Nathaniel Trask, Jesse Chan
2021	—	`conf`	Greedy Fiedler Spectral Partitioning for Data-driven Discrete Exterior Calculus. AAAI Spring Symposium: MLPS Andy Huang, Nathaniel Trask, Christopher Brissette, Xiaozhe Hu
2021	A*	`conf`	Machine learning structure preserving brackets for forecasting irreversible processes. NeurIPS Kookjin Lee, Nathaniel Trask, Panos Stinis
2021	—	`conf`	Partition of Unity Networks: Deep HP-Approximation. AAAI Spring Symposium: MLPS Kookjin Lee, Nathaniel Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr
2021	J	`jnl`	Polynomial-Spline Neural Networks with Exact Integrals. CoRR Jonas A. Actor, Andy Huang, Nathaniel Trask
2021	J	`jnl`	Probabilistic partition of unity networks: clustering based deep approximation. CoRR Nathaniel Trask, Mamikon A. Gulian, Andy Huang, Kookjin Lee
2021	J	`jnl`	Structure-preserving Sparse Identification of Nonlinear Dynamics for Data-driven Modeling. CoRR Kookjin Lee, Nathaniel Trask, Panos Stinis
2020	J	`jnl`	A conservative, consistent, and scalable meshfree mimetic method. J. Comput. Phys. Nathaniel Trask, Pavel B. Bochev, Mauro Perego
2020	J	`jnl`	A unified, stable and accurate meshfree framework for peridynamic correspondence modeling. Part I: core methods. CoRR Masoud Behzadinasab, Nathaniel Trask, Yuri Bazilevs
2020	J	`jnl`	Data-driven learning of robust nonlocal physics from high-fidelity synthetic data. CoRR Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon A. Gulian, Marta D'Elia
2020	J	`jnl`	Enforcing exact physics in scientific machine learning: a data-driven exterior calculus on graphs. CoRR Nathaniel Trask, Andy Huang, Xiaozhe Hu
2020	—	`conf`	GMLS-Nets: A Machine Learning Framework for Unstructured Data. AAAI Spring Symposium: MLPS Nathaniel Trask, Ravi G. Patel, Paul J. Atzberger, Ben J. Gross
2020	J	`jnl`	Meshfree methods on manifolds for hydrodynamic flows on curved surfaces: A Generalized Moving Least-Squares (GMLS) approach. J. Comput. Phys. Ben J. Gross, Nathaniel Trask, Paul Kuberry, Paul J. Atzberger
2019	J	`jnl`	An Asymptotically Compatible Approach For Neumann-Type Boundary Condition On Nonlocal Problems. CoRR Huaiqian You, Xin Yang Lu, Nathaniel Trask, Yue Yu
2019	J	`jnl`	Asymptotically compatible meshfree discretization of state-based peridynamics for linearly elastic composite materials. CoRR Nathaniel Trask, Benjamin Huntington, David J. Littlewood
2019	J	`jnl`	Asymptotically compatible reproducing kernel collocation and meshfree integration for nonlocal diffusion. CoRR Yu Leng, Xiaochuan Tian, Nathaniel Trask, John T. Foster
2019	J	`jnl`	GMLS-Nets: A framework for learning from unstructured data. CoRR Nathaniel Trask, Ravi G. Patel, Ben J. Gross, Paul J. Atzberger
2019	—	`conf`	Mesh-Hardened Finite Element Analysis Through a Generalized Moving Least-Squares Approximation of Variational Problems. LSSC Pavel B. Bochev, Nathaniel Trask, Paul Kuberry, Mauro Perego
2019	J	`jnl`	Meshfree Methods on Manifolds for Hydrodynamic Flows on Curved Surfaces: A Generalized Moving Least-Squares (GMLS) Approach. CoRR Ben J. Gross, Nathaniel Trask, Paul Kuberry, Paul J. Atzberger
2019	J	`jnl`	Mitigation of the self-force effect in unstructured PIC codes using generalized moving least squares. Comput. Math. Appl. Nathaniel Trask, Pavel B. Bochev, Mauro Perego
2018	J	`jnl`	A compatible high-order meshless method for the Stokes equations with applications to suspension flows. J. Comput. Phys. Nathaniel Trask, Martin R. Maxey, Xiaozhe Hu
2017	J	`jnl`	A High-Order Staggered Meshless Method for Elliptic Problems. SIAM J. Sci. Comput. Nathaniel Trask, Mauro Perego, Pavel B. Bochev
2016	J	`jnl`	Compact moving least squares: An optimization framework for generating high-order compact meshless discretizations. J. Comput. Phys. Nathaniel Trask, Martin R. Maxey, Xiaozhe Hu