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ORCIDPrasanth B. Nair
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- affiliation: University of Southampton, UK
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2020 – today
- 2023
[j13]Kevin Course
, Prasanth B. Nair:
State estimation of a physical system with unknown governing equations. Nat. 622(7982): 261-267 (2023)- [c11]Kevin Course, Prasanth B. Nair:
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs. NeurIPS 2023 - [i6]Kevin Course, Prasanth B. Nair:
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs. CoRR abs/2312.10550 (2023) - 2021
- [i5]Kevin L. Course, Trefor W. Evans, Prasanth B. Nair:
Weak Form Generalized Hamiltonian Learning. CoRR abs/2104.05096 (2021) - 2020
- [c10]Kevin Course, Trefor W. Evans, Prasanth B. Nair:
Weak Form Generalized Hamiltonian Learning. NeurIPS 2020 - [i4]Trefor W. Evans, Prasanth B. Nair:
Quadruply Stochastic Gaussian Processes. CoRR abs/2006.03015 (2020)
2010 – 2019
- 2019
- [j12]Ricardo Baptista, Valentin Stolbunov, Prasanth B. Nair:
Some greedy algorithms for sparse polynomial chaos expansions. J. Comput. Phys. 387: 303-325 (2019) - 2018
- [j11]Valentin Stolbunov, Prasanth B. Nair:
Sparse radial basis function approximation with spatially variable shape parameters. Appl. Math. Comput. 330: 170-184 (2018) - [c9]Trefor W. Evans, Prasanth B. Nair:
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF). ICML 2018: 1416-1425 - [c8]Trefor W. Evans, Prasanth B. Nair:
Discretely Relaxing Continuous Variables for tractable Variational Inference. NeurIPS 2018: 10487-10497 - [c7]Trefor W. Evans, Prasanth B. Nair:
Exploiting Structure for Fast Kernel Learning. SDM 2018: 414-422 - [i3]Trefor W. Evans, Prasanth B. Nair:
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF). CoRR abs/1807.02125 (2018) - [i2]Trefor W. Evans, Prasanth B. Nair:
Exploiting Structure for Fast Kernel Learning. CoRR abs/1808.03351 (2018) - [i1]Trefor W. Evans, Prasanth B. Nair:
Discretely Relaxing Continuous Variables for tractable Variational Inference. CoRR abs/1809.04279 (2018) - 2016
- [j10]Wei W. Xing, Vasileios Triantafyllidis, Akeel A. Shah, Prasanth B. Nair, Nicholas Zabaras:
Manifold learning for the emulation of spatial fields from computational models. J. Comput. Phys. 326: 666-690 (2016)
2000 – 2009
- 2009
- [c6]Phani Chinchapatnam, Kawal S. Rhode, Matthew Ginks, Prasanth B. Nair, Reza Razavi, Simon R. Arridge, Maxime Sermesant:
Voxel Based Adaptive Meshless Method for Cardiac Electrophysiology Simulation. FIMH 2009: 182-190 - 2008
- [j9]Yew-Soon Ong, Kai Yew Lum, Prasanth B. Nair:
Hybrid evolutionary algorithm with Hermite radial basis function interpolants for computationally expensive adjoint solvers. Comput. Optim. Appl. 39(1): 97-119 (2008) - [j8]Vijaya B. Kolachalama, Neil W. Bressloff, Prasanth B. Nair, Clifford P. Shearman:
Predictive Haemodynamics in a One-Dimensional Human Carotid Artery Bifurcation. Part II: Application to Graft Design. IEEE Trans. Biomed. Eng. 55(3): 1176-1184 (2008) - [j7]Andras Sobester, Prasanth B. Nair, Andy J. Keane:
Genetic Programming Approaches for Solving Elliptic Partial Differential Equations. IEEE Trans. Evol. Comput. 12(4): 469-478 (2008) - 2007
- [j6]Phani Chinchapatnam, Kamal Djidjeli, Prasanth B. Nair:
Pointwise uniformly convergent numerical treatment for the non-stationary Burger-Huxley equation using grid equidistribution. Int. J. Comput. Math. 84(10): 1509-1521 (2007) - [j5]Vijaya B. Kolachalama, Neil W. Bressloff, Prasanth B. Nair, Clifford P. Shearman:
Predictive Haemodynamics in a One-Dimensional Human Carotid Artery Bifurcation. Part I: Application to Stent Design. IEEE Trans. Biomed. Eng. 54(5): 802-812 (2007) - [j4]Zongzhao Zhou, Yew-Soon Ong, Prasanth B. Nair, Andy J. Keane, Kai Yew Lum:
Combining Global and Local Surrogate Models to Accelerate Evolutionary Optimization. IEEE Trans. Syst. Man Cybern. Part C 37(1): 66-76 (2007) - 2006
- [j3]Arindam Choudhury, Prasanth B. Nair, Andy J. Keane:
Constructing a speculative kernel machine for pattern classification. Neural Networks 19(1): 84-89 (2006) - [j2]Yew-Soon Ong, Prasanth B. Nair, Kai Yew Lum:
Max-min surrogate-assisted evolutionary algorithm for robust design. IEEE Trans. Evol. Comput. 10(4): 392-404 (2006) - 2004
- [c5]Zongzhao Zhou, Yew-Soon Ong, Prasanth B. Nair:
Hierarchical surrogate-assisted evolutionary optimization framework. IEEE Congress on Evolutionary Computation 2004: 1586-1593 - 2003
- [c4]Yew-Soon Ong, Kai Yew Lum, Prasanth B. Nair, Daming Shi, Z. K. Zhang:
Global convergence of unconstrained and bound constrained surrogate-assisted evolutionary search in aerodynamic shape design. IEEE Congress on Evolutionary Computation 2003: 1856-1863 - 2002
- [j1]Prasanth B. Nair, Arindam Choudhury, Andy J. Keane:
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels. J. Mach. Learn. Res. 3: 781-801 (2002) - [c3]Arindam Choudhury, Prasanth B. Nair, Andy J. Keane:
A Data Parallel Approach for Large-Scale Gaussian Process Modeling. SDM 2002: 95-111 - 2001
- [c2]Prasanth B. Nair, Arindam Choudhury, Andy J. Keane:
Some Greedy Algorithms for Sparse Nonlinear Regression. ICML 2001: 369-376
1990 – 1999
- 1999
- [c1]Mohammed El-Beltagy, Prasanth B. Nair, Andy J. Keane:
Metamodeling Techniques For Evolutionary Optimization of Computationally Expensive Problems: Promises and Limitations. GECCO 1999: 196-203
Coauthor Index
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