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ORCIDRobert M. Kirby
Robert Michael Kirby – Mike Kirby
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- affiliation: University of Utah, Salt Lake City, UT, USA
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2020 – today
- 2024
[j112]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: 107615 (2024)- [j111]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: 113238 (2024) - [j110]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): 8:1-8:31 (2024) - [c82]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: 2413-2421 - [c81]Shibo Li, Xin Yu, Wei W. Xing, Robert M. Kirby, Akil Narayan, Shandian Zhe:
Multi-Resolution Active Learning of Fourier Neural Operators. AISTATS 2024: 2440-2448 - [c80]Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe:
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. ICLR 2024 - [c79]Shikai Fang, Madison Cooley, Da Long, Shibo Li, Mike Kirby, Shandian Zhe:
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. ICLR 2024 - [i61]Michael Penwarden, Houman Owhadi, Robert M. Kirby:
Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics. CoRR abs/2402.11126 (2024) - [i60]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 abs/2406.02336 (2024) - [i59]Zachary Bastiani, Robert M. Kirby, Jacob D. Hochhalter, Shandian Zhe:
Complexity-Aware Deep Symbolic Regression with Robust Risk-Seeking Policy Gradients. CoRR abs/2406.06751 (2024) - 2023
- [j109]Ben Charoenwong, Robert M. Kirby, Jonathan Reiter:
Computer Science Abstractions to Help Reason About Decentralized Stablecoin Design. IEEE Access 11: 103201-103213 (2023) - [j108]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: 111912 (2023) - [j107]Vidhi Zala, Akil Narayan, Robert M. Kirby:
Convex optimization-based structure-preserving filter for multidimensional finite element simulations. J. Comput. Phys. 492: 112364 (2023) - [j106]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: 112464 (2023) - [j105]T. A. J. Ouermi, Robert M. Kirby, Martin Berzins:
ENO-based high-order data-bounded and constrained positivity-preserving interpolation. Numer. Algorithms 92(3): 1517-1551 (2023) - [c78]Shibo Li, Zheng Wang, Akil Narayan, Robert M. Kirby, Shandian Zhe:
Meta-Learning with Adjoint Methods. AISTATS 2023: 7239-7251 - [c77]Ben Charoenwong, Robert M. Kirby, Jonathan Reiter:
Risk-Free Interest Rates in Decentralized Finance. BCCA 2023: 466-473 - [c76]Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami:
Adaptive Self-Supervision Algorithms for Physics-Informed Neural Networks. ECAI 2023: 2234-2241 - [c75]Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe:
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML 2023: 19855-19881 - [c74]Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Mike Kirby, Shandian Zhe:
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. NeurIPS 2023 - [i58]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 abs/2302.00807 (2023) - [i57]Hongsup Oh, Roman Amici, Geoffrey F. Bomarito, Shandian Zhe, Robert M. Kirby, Jacob D. Hochhalter:
Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations. CoRR abs/2302.03175 (2023) - [i56]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 abs/2302.14227 (2023) - [i55]Haocheng Dai, Michael Penwarden, Robert M. Kirby, Sarang C. Joshi:
Neural Operator Learning for Ultrasound Tomography Inversion. CoRR abs/2304.03297 (2023) - [i54]Shibo Li, Xin Yu, Wei W. Xing, Mike Kirby, Akil Narayan, Shandian Zhe:
Multi-Resolution Active Learning of Fourier Neural Operators. CoRR abs/2309.16971 (2023) - [i53]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 abs/2310.05387 (2023) - [i52]Timbwaoga A. J. Ouermi, Robert M. Kirby, Martin Berzins:
Algorithm xxxx: HiPPIS A High-Order Positivity-Preserving Mapping Software for Structured Meshes. CoRR abs/2310.08818 (2023) - [i51]Shikai Fang, Xin Yu, Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe:
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. CoRR abs/2310.17021 (2023) - [i50]Shikai Fang, Madison Cooley, Da Long, Shibo Li, Robert M. Kirby, Shandian Zhe:
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes. CoRR abs/2311.04465 (2023) - [i49]Shikai Fang, Xin Yu, Zheng Wang, Shibo Li, Mike Kirby, Shandian Zhe:
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data. CoRR abs/2311.04829 (2023) - 2022
- [j104]Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby:
Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. 451: 110844 (2022) - [j103]Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey:
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. J. Sci. Comput. 90(2): 78 (2022) - [j102]Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan:
A Bandit-Learning Approach to Multifidelity Approximation. SIAM J. Sci. Comput. 44(1): 150- (2022) - [j101]Nghia Truong, Cem Yuksel, Chakrit Watcharopas, Joshua A. Levine, Robert M. Kirby:
Particle Merging-and-Splitting. IEEE Trans. Vis. Comput. Graph. 28(12): 4546-4557 (2022) - [c73]Zheng Wang, Wei W. Xing, Robert M. Kirby, Shandian Zhe:
Physics Informed Deep Kernel Learning. AISTATS 2022: 1206-1218 - [c72]Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe:
Deep Multi-Fidelity Active Learning of High-Dimensional Outputs. AISTATS 2022: 1694-1711 - [c71]Shikai Fang, Akil Narayan, Robert M. Kirby, Shandian Zhe:
Bayesian Continuous-Time Tucker Decomposition. ICML 2022: 6235-6245 - [c70]Shibo Li, Robert M. Kirby, Shandian Zhe:
Decomposing Temporal High-Order Interactions via Latent ODEs. ICML 2022: 12797-12812 - [c69]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: 14210-14222 - [c68]Han D. Tran, Milinda Fernando, Kumar Saurabh, Baskar Ganapathysubramanian, Robert M. Kirby, Hari Sundar:
A scalable adaptive-matrix SPMV for heterogeneous architectures. IPDPS 2022: 13-24 - [c67]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: 189-204 - [c66]Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe:
Infinite-Fidelity Coregionalization for Physical Simulation. NeurIPS 2022 - [c65]Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Active Learning with Budget Constraints. NeurIPS 2022 - [i48]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 abs/2201.00888 (2022) - [i47]Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna C. 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 abs/2202.04137 (2022) - [i46]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 abs/2202.12316 (2022) - [i45]Vidhi Zala, Akil Narayan, Robert M. Kirby:
Convex Optimization-Based Structure-Preserving Filter For Multidimensional Finite Element Simulations. CoRR abs/2203.09748 (2022) - [i44]Jarom D. Hogue, Robert M. Kirby, Akil Narayan:
Dimensionality Reduction in Deep Learning via Kronecker Multi-layer Architectures. CoRR abs/2204.04273 (2022) - [i43]Timbwaoga A. J. Ouermi, Robert M. Kirby, Martin Berzins:
ENO-Based High-Order Data-Bounded and Constrained Positivity-Preserving Interpolation. CoRR abs/2204.06168 (2022) - [i42]Shibo Li, Zheng Wang, Robert M. Kirby, Shandian Zhe:
Infinite-Fidelity Coregionalization for Physical Simulation. CoRR abs/2207.00678 (2022) - [i41]Shashank Subramanian, Robert M. Kirby, Michael W. Mahoney, Amir Gholami:
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks. CoRR abs/2207.04084 (2022) - [i40]Tan M. 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 abs/2208.00579 (2022) - [i39]Shibo Li, Michael Penwarden, Robert M. Kirby, Shandian Zhe:
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. CoRR abs/2210.12669 (2022) - [i38]Shibo Li, Jeff M. Phillips, Xin Yu, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Active Learning with Budget Constraints. CoRR abs/2210.12704 (2022) - 2021
- [j100]Vahid Keshavarzzadeh, Mitra Alirezaei, Tolga Tasdizen, Robert M. Kirby:
Image-Based Multiresolution Topology Optimization Using Deep Disjunctive Normal Shape Model. Comput. Aided Des. 130: 102947 (2021) - [j99]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: 107695 (2021) - [j98]Wei W. Xing, Robert M. Kirby, Shandian Zhe:
Deep coregionalization for the emulation of simulation-based spatial-temporal fields. J. Comput. Phys. 428: 109984 (2021) - [j97]Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan:
Multilevel Designed Quadrature for Partial Differential Equations with Random Inputs. SIAM J. Sci. Comput. 43(2): A1412-A1440 (2021) - [j96]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): A3713-A3732 (2021) - [j95]Valerio Pascucci, Mike Kirby:
Message from VIS 2020 General Chairs. IEEE Trans. Vis. Comput. Graph. 27(2): xvii (2021) - [j94]Harsh Bhatia, Robert M. Kirby, Valerio Pascucci, Peer-Timo Bremer:
Vector Field Decompositions Using Multiscale Poisson Kernel. IEEE Trans. Vis. Comput. Graph. 27(9): 3781-3793 (2021) - [c64]Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe:
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. AISTATS 2021: 847-855 - [c63]Majid Rasouli, Robert M. Kirby, Hari Sundar:
A Compressed, Divide and Conquer Algorithm for Scalable Distributed Matrix-Matrix Multiplication. HPC Asia 2021: 110-119 - [c62]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: 235-248 - [c61]Shibo Li, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. NeurIPS 2021: 25463-25475 - [c60]Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney:
Characterizing possible failure modes in physics-informed neural networks. NeurIPS 2021: 26548-26560 - [c59]Shikai Fang, Robert M. Kirby, Shandian Zhe:
Bayesian streaming sparse Tucker decomposition. UAI 2021: 558-567 - [i37]Mani Razi, Robert M. Kirby, Akil Narayan:
Kernel optimization for Low-Rank Multi-Fidelity Algorithms. CoRR abs/2101.01769 (2021) - [i36]Edward Laughton, Vidhi Zala, Akil Narayan, Robert M. Kirby, David Moxey:
Fast Barycentric-Based Evaluation Over Spectral/hp Elements. CoRR abs/2103.03594 (2021) - [i35]Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan:
A bandit-learning approach to multifidelity approximation. CoRR abs/2103.15342 (2021) - [i34]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 abs/2104.03743 (2021) - [i33]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 abs/2104.14704 (2021) - [i32]Vidhi Zala, Robert M. Kirby, Akil Narayan:
Structure-preserving Nonlinear Filtering for Continuous and Discontinuous Galerkin Spectral/hp Element Methods. CoRR abs/2106.08316 (2021) - [i31]Shibo Li, Robert M. Kirby, Shandian Zhe:
Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks. CoRR abs/2106.09884 (2021) - [i30]Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby:
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR abs/2106.13361 (2021) - [i29]Nghia Truong, Cem Yuksel, Chakrit Watcharopas, Joshua A. Levine, Robert M. Kirby:
Particle Merging-and-Splitting. CoRR abs/2107.08093 (2021) - [i28]Aditi S. Krishnapriyan, Amir Gholami, Shandian Zhe, Robert M. Kirby, Michael W. Mahoney:
Characterizing possible failure modes in physics-informed neural networks. CoRR abs/2109.01050 (2021) - [i27]Shibo Li, Zheng Wang, Akil Narayan, Robert Michael Kirby, Shandian Zhe:
Meta-Learning with Adjoint Methods. CoRR abs/2110.08432 (2021) - [i26]Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby:
Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR abs/2110.13361 (2021) - 2020
- [j93]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. Comput. Phys. Commun. 249: 107110 (2020) - [j92]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) - [j91]David Moxey, Roman Amici, Mike Kirby:
Efficient Matrix-Free High-Order Finite Element Evaluation for Simplicial Elements. SIAM J. Sci. Comput. 42(3): C97-C123 (2020) - [j90]Vidhi Zala, Mike Kirby, Akil Narayan:
Structure-Preserving Function Approximation via Convex Optimization. SIAM J. Sci. Comput. 42(5): A3006-A3029 (2020) - [j89]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): 162-172 (2020) - [c58]Wei W. Xing, Shireen Y. Elhabian, Robert Michael Kirby, Ross T. Whitaker, Shandian Zhe:
Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations. AAAI 2020: 6462-6469 - [c57]Max Carlson, Robert M. Kirby, Hari Sundar:
A scalable framework for solving fractional diffusion equations. ICS 2020: 2:1-2:11 - [c56]Shibo Li, Wei W. Xing, Robert M. Kirby, Shandian Zhe:
Scalable Gaussian Process Regression Networks. IJCAI 2020: 2456-2462 - [c55]Shibo Li, Wei W. Xing, Robert M. Kirby, Shandian Zhe:
Multi-Fidelity Bayesian Optimization via Deep Neural Networks. NeurIPS 2020 - [i25]Shibo Li, Wei W. Xing, Mike Kirby, Shandian Zhe:
Scalable Variational Gaussian Process Regression Networks. CoRR abs/2003.11489 (2020) - [i24]Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe:
Multi-Fidelity High-Order Gaussian Processes for Physical Simulation. CoRR abs/2006.04972 (2020) - [i23]Zheng Wang, Wei W. Xing, Robert Michael Kirby, Shandian Zhe:
Physics Regularized Gaussian Processes. CoRR abs/2006.04976 (2020) - [i22]Shibo Li, Wei W. Xing, Mike Kirby, Shandian Zhe:
Multi-Fidelity Bayesian Optimization via Deep Neural Networks. CoRR abs/2007.03117 (2020) - [i21]Vidhi Zala, Robert M. Kirby, Akil Narayan:
Structure-preserving function approximation via convex optimization. CoRR abs/2008.08223 (2020) - [i20]T. A. J. Ouermi, Robert M. Kirby, Martin Berzins:
Numerical Testing of a New Positivity-Preserving Interpolation Algorithm. CoRR abs/2009.08535 (2020) - [i19]Shibo Li, Robert M. Kirby, Shandian Zhe:
Deep Multi-Fidelity Active Learning of High-dimensional Outputs. CoRR abs/2012.00901 (2020) - [i18]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 abs/2012.14901 (2020)
2010 – 2019
- 2019
- [j88]Mani Razi, Robert M. Kirby, Akil Narayan:
Fast predictive multi-fidelity prediction with models of quantized fidelity levels. J. Comput. Phys. 376: 992-1008 (2019) - [j87]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: 732-744 (2019) - [j86]David Moxey, Shankar P. Sastry, Robert M. Kirby:
Interpolation Error Bounds for Curvilinear Finite Elements and Their Implications on Adaptive Mesh Refinement. J. Sci. Comput. 78(2): 1045-1062 (2019) - [j85]Ashok Jallepalli, Robert Haimes, Robert M. Kirby:
Adaptive Characteristic Length for L-SIAC Filtering of FEM Data. J. Sci. Comput. 79(1): 542-563 (2019) - [j84]Ashok Jallepalli, Robert M. Kirby:
Efficient Algorithms for the Line-SIAC Filter. J. Sci. Comput. 80(2): 743-761 (2019) - [j83]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): 1150-1180 (2019) - [j82]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): 203-231 (2019) - [j81]Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan:
Convergence Acceleration for Time-Dependent Parametric Multifidelity Models. SIAM J. Numer. Anal. 57(3): 1344-1368 (2019) - [c54]Shandian Zhe, Wei W. Xing, Robert M. Kirby:
Scalable High-Order Gaussian Process Regression. AISTATS 2019: 2611-2620 - [c53]Majid Rasouli, Vidhi Zala, Robert M. Kirby, Hari Sundar:
Scalable Lazy-update Multigrid Preconditioners. HPEC 2019: 1-7 - [c52]Jian Wang, Wei W. Xing, Robert M. Kirby, Miaomiao Zhang:
Data-Driven Model Order Reduction for Diffeomorphic Image Registration. IPMI 2019: 694-705 - [i17]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 abs/1906.03489 (2019) - [i16]Ashok Jallepalli, Joshua A. Levine, Robert M. Kirby:
The Effect of Data Transformations on Scalar Field Topological Analysis of High-Order FEM Solutions. CoRR abs/1907.07224 (2019) - [i15]Wei W. Xing, Robert M. Kirby, Shandian Zhe:
Deep Coregionalization for the Emulation of Spatial-Temporal Fields. CoRR abs/1910.07577 (2019) - [i14]Max Carlson, Robert M. Kirby, Hari Sundar:
A Scalable Framework for Solving Fractional Diffusion Equations. CoRR abs/1911.11906 (2019) - [i13]Christoph Heinzl, Robert Michael Kirby, Stepan V. Lomov, Guillermo Requena, Rüdiger Westermann:
Visual Computing in Materials Sciences (Dagstuhl Seminar 19151). Dagstuhl Reports 9(4): 1-42 (2019) - 2018
- [j80]Thomas Torsney-Weir, Torsten Möller, Michael Sedlmair, Robert M. Kirby:
Hypersliceplorer: Interactive visualization of shapes in multiple dimensions. Comput. Graph. Forum 37(3): 229-240 (2018) - [j79]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): 301-327 (2018) - [j78]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: 732-750 (2018) - [j77]Varun Shankar, Akil Narayan, Robert M. Kirby:
RBF-LOI: Augmenting Radial Basis Functions (RBFs) with Least Orthogonal Interpolation (LOI) for solving PDEs on surfaces. J. Comput. Phys. 373: 722-735 (2018) - [j76]Vidhi Zala, Varun Shankar, Shankar P. Sastry, Robert M. Kirby:
Curvilinear Mesh Adaptation Using Radial Basis Function Interpolation and Smoothing. J. Sci. Comput. 77(1): 397-418 (2018) - [j75]Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan:
Numerical Integration in Multiple Dimensions with Designed Quadrature. SIAM J. Sci. Comput. 40(4): A2033-A2061 (2018) - [j74]Varun Shankar, Robert M. Kirby, Aaron L. Fogelson:
Robust Node Generation for Mesh-free Discretizations on Irregular Domains and Surfaces. SIAM J. Sci. Comput. 40(4): A2584-A2608 (2018) - [j73]