Robert M. Kirby

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 118

Top Venues

CoRR

J. Sci. Comput.

J. Comput. Phys.

IEEE Trans. Vis. Comput. Graph.

Publications

Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. CoRR (2024)
Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe
Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS (2024)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. AISTATS (2024)
Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
Deep neural operators as accurate surrogates for shape optimization. Eng. Appl. Artif. Intell. 129 (2024)
Ashok Jallepalli, Marshall C. Galbraith, Robert Haimes, Robert M. Kirby
Non-uniform knot (NUK) SIAC post-processing of flow fields produced through unstructured grid adaptation and optimization. J. Comput. Phys. 514 (2024)
Madison Cooley, Shandian Zhe, Robert M. Kirby, Varun Shankar
Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation. CoRR (2024)
Timbwoga A. J. Ouermi, Robert M. Kirby, Martin Berzins
Algorithm 1041: HiPPIS - A High-order Positivity-preserving Mapping Software for Structured Meshes. ACM Trans. Math. Softw. 50 (1) (2024)
Michael Penwarden, Houman Owhadi, Robert M. Kirby
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics. CoRR (2024)
Timbwaoga A. J. Ouermi, Robert M. Kirby, Martin Berzins
Algorithm xxxx: HiPPIS A High-Order Positivity-Preserving Mapping Software for Structured Meshes. CoRR (2023)
Da Long, Wei W. Xing, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
Equation Discovery with Bayesian Spike-and-Slab Priors and Efficient Kernels. CoRR (2023)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. 477 (2023)
Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Meta-Learning with Adjoint Methods. AISTATS (2023)
Haocheng Dai, Michael Penwarden, Robert M. Kirby, Sarang C. Joshi
Neural Operator Learning for Ultrasound Tomography Inversion. CoRR (2023)
Ben Charoenwong, Robert M. Kirby, Jonathan Reiter
Computer Science Abstractions to Help Reason About Decentralized Stablecoin Design. IEEE Access 11 (2023)
Ben Charoenwong, Robert M. Kirby, Jonathan Reiter
Risk-Free Interest Rates in Decentralized Finance. BCCA (2023)
T. A. J. Ouermi, Robert M. Kirby, Martin Berzins
ENO-based high-order data-bounded and constrained positivity-preserving interpolation. Numer. Algorithms 92 (3) (2023)
Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. CoRR (2023)
Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. CoRR (2023)
Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils. CoRR (2023)
Vidhi Zala, Akil Narayan, Robert M. Kirby
Convex optimization-based structure-preserving filter for multidimensional finite element simulations. J. Comput. Phys. 492 (2023)
Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. CoRR (2023)
Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. J. Comput. Phys. 493 (2023)
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI (2023)
Vidhi Zala, Akil Narayan, Robert M. Kirby
Convex Optimization-Based Structure-Preserving Filter For Multidimensional Finite Element Simulations. CoRR (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Infinite-Fidelity Coregionalization for Physical Simulation. CoRR (2022)
Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks. CoRR (2022)
Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna Garikipati, Lori Graham-Brady, Amanda A. Howard, George Em Karniadakis, Vahid Keshavarzzadeh, Robert M. Kirby, J. Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Hamdi A. Tchelepi, Bozo Vazic, Hari S. Viswanathan, Hongkyu Yoon, Piotr Zarzycki
Machine Learning in Heterogeneous Porous Materials. CoRR (2022)
Han D. Tran, Milinda Fernando, Kumar Saurabh, Baskar Ganapathysubramanian, Robert M. Kirby, Hari Sundar
A scalable adaptive-matrix SPMV for heterogeneous architectures. IPDPS (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. CoRR (2022)
Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML (2022)
Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Active Learning with Budget Constraints. CoRR (2022)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. 451 (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Infinite-Fidelity Coregionalization for Physical Simulation. NeurIPS (2022)
Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. J. Sci. Comput. 90 (2) (2022)
Timbwaoga A. J. Ouermi, Robert M. Kirby, Martin Berzins
ENO-Based High-Order Data-Bounded and Constrained Positivity-Preserving Interpolation. CoRR (2022)
Nghia Truong, Cem Yuksel, Chakrit Watcharopas, Joshua A. Levine, Robert M. Kirby
Particle Merging-and-Splitting. IEEE Trans. Vis. Comput. Graph. 28 (12) (2022)
Tan Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. CoRR (2022)
Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
A Bandit-Learning Approach to Multifidelity Approximation. SIAM J. Sci. Comput. 44 (1) (2022)
Jarom D. Hogue, Robert M. Kirby, Akil Narayan
Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures. CoRR (2022)
Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Active Learning with Budget Constraints. NeurIPS (2022)
Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe
Bayesian Continuous-Time Tucker Decomposition. ICML (2022)
Shibo Li, Michael Penwarden, Robert M. Kirby, Shandian Zhe
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. CoRR (2022)
Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe
Deep Multi-Fidelity Active Learning of High-Dimensional Outputs. AISTATS (2022)
Zheng Wang, Wei Xing, Robert M. Kirby, Shandian Zhe
Physics Informed Deep Kernel Learning. AISTATS (2022)
Vahid Keshavarzzadeh, Shandian Zhe, Robert M. Kirby, Akil Narayan
GP-HMAT: Scalable, O(n log(n)) Gaussian Process Regression with Hierarchical Low-Rank Matrices. CoRR (2022)
Da Long, Zheng Wang, Aditi S. Krishnapriyan, Robert M. Kirby, Shandian Zhe, Michael W. Mahoney
AutoIP: A United Framework to Integrate Physics into Gaussian Processes. ICML (2022)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs. SIAM J. Sci. Comput. 43 (2) (2021)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. CoRR (2021)
Shibo Li, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. NeurIPS (2021)
Harsh Bhatia, Steve Petruzza, Rushil Anirudh, Attila Gyulassy, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer
Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows. ISVC (1) (2021)
Wei W. Xing, Akeel A. Shah, Peng Wang, Shandian Zhe, Qian Fu, Robert M. Kirby
Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations. CoRR (2021)
Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
A bandit-learning approach to multifidelity approximation. CoRR (2021)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-Preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. SIAM J. Sci. Comput. 43 (6) (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR (2021)
Shikai Fang, Robert M. Kirby, Shandian Zhe
Bayesian streaming sparse Tucker decomposition. UAI (2021)
Nghia Truong, Cem Yuksel, Chakrit Watcharopas, Joshua A. Levine, Robert M. Kirby
Particle Merging-and-Splitting. CoRR (2021)
Mani Razi, Robert M. Kirby, Akil Narayan
Kernel optimization for Low-Rank Multi-Fidelity Algorithms. CoRR (2021)
Majid Rasouli, Robert M. Kirby, Hari Sundar
A Compressed, Divide and Conquer Algorithm for Scalable Distributed Matrix-Matrix Multiplication. HPC Asia (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. CoRR (2021)
Vahid Keshavarzzadeh, Mitra Alirezaei, Tolga Tasdizen, Robert M. Kirby
Image-Based Multiresolution Topology Optimization Using Deep Disjunctive Normal Shape Model. Comput. Aided Des. 130 (2021)
Harsh Bhatia, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer
Vector Field Decompositions Using Multiscale Poisson Kernel. IEEE Trans. Vis. Comput. Graph. 27 (9) (2021)
Shibo Li, Robert M. Kirby, Shandian Zhe
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. CoRR (2021)
Max Carlson, Xiaoning Zheng, Hari Sundar, George Em Karniadakis, Robert M. Kirby
An open-source parallel code for computing the spectral fractional Laplacian on 3D complex geometry domains. Comput. Phys. Commun. 261 (2021)
M. Keith Ballard, Roman Amici, Varun Shankar, Lauren A. Ferguson, Michael Braginsky, Robert M. Kirby
Towards an Extrinsic, CG-XFEM Approach Based on Hierarchical Enrichments for Modeling Progressive Fracture. CoRR (2021)
Wei W. Xing, Robert M. Kirby, Shandian Zhe
Deep coregionalization for the emulation of simulation-based spatial-temporal fields. J. Comput. Phys. 428 (2021)
Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney
Characterizing possible failure modes in physics-informed neural networks. NeurIPS (2021)
Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. CoRR (2021)
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR (2021)
Max Carlson, Robert M. Kirby, Hari Sundar
A scalable framework for solving fractional diffusion equations. ICS (2020)
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Multi-Fidelity Bayesian Optimization via Deep Neural Networks. NeurIPS (2020)
David Moxey, Chris D. Cantwell, Yan Bao, Andrea Cassinelli, Giacomo Castiglioni, Sehun Chun, Emilia Juda, Ehsan Kazemi, Kilian Lackhove, Julian Marcon, Gianmarco Mengaldo, Douglas Serson, Michael Turner, Hui Xu, Joaquim Peiró, Robert M. Kirby, Spencer J. Sherwin
++: Enhancing the capability and application of high-fidelity spectral/hp element methods. Comput. Phys. Commun. 249 (2020)
Ashok Jallepalli, Joshua A. Levine, Robert M. Kirby
The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions. IEEE Trans. Vis. Comput. Graph. 26 (1) (2020)
Shibo Li, Wei Xing, Robert M. Kirby, Shandian Zhe
Scalable Gaussian Process Regression Networks. IJCAI (2020)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Generation of nested quadrature rules for generic weight functions via numerical optimization: Application to sparse grids. J. Comput. Phys. 400 (2020)
T. A. J. Ouermi, Robert M. Kirby, Martin Berzins
Numerical Testing of a New Positivity-Preserving Interpolation Algorithm. CoRR (2020)
Daniel J. Perry, Vahid Keshavarzzadeh, Shireen Y. Elhabian, Robert M. Kirby, Michael Gleicher, Ross T. Whitaker
Visualization of topology optimization designs with representative subset selection. CoRR (2020)
Vidhi Zala, Robert M. Kirby, Akil Narayan
Structure-preserving function approximation via convex optimization. CoRR (2020)
Shibo Li, Robert M. Kirby, Shandian Zhe
Deep Multi-Fidelity Active Learning of High-dimensional Outputs. CoRR (2020)
Ashok Jallepalli, Joshua A. Levine, Robert M. Kirby
The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions. CoRR (2019)
Ashok Jallepalli, Robert Haimes, Robert M. Kirby
Adaptive Characteristic Length for L-SIAC Filtering of FEM Data. J. Sci. Comput. 79 (1) (2019)
Ashok Jallepalli, Robert M. Kirby
Efficient Algorithms for the Line-SIAC Filter. J. Sci. Comput. 80 (2) (2019)
Mani Razi, Robert M. Kirby, Akil Narayan
Fast predictive multi-fidelity prediction with models of quantized fidelity levels. J. Comput. Phys. 376 (2019)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Convergence Acceleration for Time-Dependent Parametric Multifidelity Models. SIAM J. Numer. Anal. 57 (3) (2019)
Majid Rasouli, Vidhi Zala, Robert M. Kirby, Hari Sundar
Scalable Lazy-update Multigrid Preconditioners. HPEC (2019)
David Moxey, Shankar Prasad Sastry, Robert M. Kirby
Interpolation Error Bounds for Curvilinear Finite Elements and Their Implications on Adaptive Mesh Refinement. J. Sci. Comput. 78 (2) (2019)
David Moxey, Chris D. Cantwell, Yan Bao, Andrea Cassinelli, Giacomo Castiglioni, Sehun Chun, Emilia Juda, Ehsan Kazemi, Kilian Lackhove, Julian Marcon, Gianmarco Mengaldo, Douglas Serson, Michael Turner, Hui Xu, Joaquim Peiró, Robert M. Kirby, Spencer J. Sherwin
Nektar++: enhancing the capability and application of high-fidelity spectral/hp element methods. CoRR (2019)
Xiaozhou Li, Jennifer K. Ryan, Robert M. Kirby, Kees Vuik
Smoothness-Increasing Accuracy-Conserving (SIAC) Filtering for Discontinuous Galerkin Solutions over Nonuniform Meshes: Superconvergence and Optimal Accuracy. J. Sci. Comput. 81 (3) (2019)
Daniel J. Perry, Robert M. Kirby, Akil Narayan, Ross T. Whitaker
Allocation Strategies for High Fidelity Models in the Multifidelity Regime. SIAM/ASA J. Uncertain. Quantification 7 (1) (2019)
Jian Wang, Wei Xing, Robert M. Kirby, Miaomiao Zhang
Data-Driven Model Order Reduction for Diffeomorphic Image Registration. IPMI (2019)
Shandian Zhe, Wei Xing, Robert M. Kirby
Scalable High-Order Gaussian Process Regression. AISTATS (2019)
Martin Vymazal, David Moxey, Chris D. Cantwell, Spencer J. Sherwin, Robert M. Kirby
On weak Dirichlet boundary conditions for elliptic problems in the continuous Galerkin method. J. Comput. Phys. 394 (2019)
Max Carlson, Robert M. Kirby, Hari Sundar
A Scalable Framework for Solving Fractional Diffusion Equations. CoRR (2019)
Wei Xing, Robert M. Kirby, Shandian Zhe
Deep Coregionalization for the Emulation of Spatial-Temporal Fields. CoRR (2019)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Numerical Integration in Multiple Dimensions with Designed Quadrature. SIAM J. Sci. Comput. 40 (4) (2018)
Anindya Bhaduri, Yanyan He, Michael D. Shields, Lori Graham-Brady, Robert M. Kirby
Stochastic collocation approach with adaptive mesh refinement for parametric uncertainty analysis. J. Comput. Phys. 371 (2018)
T. A. J. Ouermi, Robert M. Kirby, Martin Berzins
Performance Optimization Strategies for WRF Physics Schemes Used in Weather Modeling. Int. J. Netw. Comput. 8 (2) (2018)
Marc Rautenhaus, Michael Böttinger, Stephan Siemen, Robert Hoffman, Robert M. Kirby, Mahsa Mirzargar, Niklas Röber, Rüdiger Westermann
Visualization in Meteorology - A Survey of Techniques and Tools for Data Analysis Tasks. IEEE Trans. Vis. Comput. Graph. 24 (12) (2018)
Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan
Numerical Integration in Multiple Dimensions with Designed Quadrature. CoRR (2018)
Vidhi Zala, Varun Shankar, Shankar Prasad Sastry, Robert M. Kirby
Curvilinear Mesh Adaptation Using Radial Basis Function Interpolation and Smoothing. J. Sci. Comput. 77 (1) (2018)
Ashok Jallepalli, Julia Docampo-Sánchez, Jennifer K. Ryan, Robert Haimes, Robert M. Kirby
On the Treatment of Field Quantities and Elemental Continuity in FEM Solutions. IEEE Trans. Vis. Comput. Graph. 24 (1) (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Robert M. Kirby