Prasanth B. Nair

According to our database, Prasanth B. Nair authored at least 26 papers between 1999 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Robust Level-Set-Based Topology Optimization Under Uncertainties Using Anchored ANOVA Petrov-Galerkin Method.

Christophe Audouze, Aaron Klein, Adrian Butscher, Nigel J. W. Morris, Prasanth Nair, Masayuki Yano

SIAM/ASA J. Uncertain. Quantification, September, 2023

State estimation of a physical system with unknown governing equations.

Kevin Course, Prasanth B. Nair

Nat., 2023

Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs.

Kevin Course, Prasanth B. Nair

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2020

Quadruply Stochastic Gaussian Processes.

Trefor W. Evans, Prasanth B. Nair

CoRR, 2020

Weak Form Generalized Hamiltonian Learning.

Kevin Course, Trefor W. Evans, Prasanth B. Nair

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Some greedy algorithms for sparse polynomial chaos expansions.

Ricardo Baptista, Valentin Stolbunov, Prasanth B. Nair

J. Comput. Phys., 2019

2018

Sparse radial basis function approximation with spatially variable shape parameters.

Valentin Stolbunov, Prasanth B. Nair

Appl. Math. Comput., 2018

Exploiting Structure for Fast Kernel Learning.

Trefor W. Evans, Prasanth B. Nair

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Discretely Relaxing Continuous Variables for tractable Variational Inference.

Trefor W. Evans, Prasanth B. Nair

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF).

Trefor W. Evans, Prasanth B. Nair

Proceedings of the 35th International Conference on Machine Learning, 2018

2016

Manifold learning for the emulation of spatial fields from computational models.

Wei W. Xing, Vasileios Triantafyllidis, Akeel A. Shah, Prasanth B. Nair, Nicholas Zabaras

J. Comput. Phys., 2016

2009

Voxel Based Adaptive Meshless Method for Cardiac Electrophysiology Simulation.

Phani Chinchapatnam, Kawal S. Rhode, Matthew Ginks, Prasanth B. Nair, Reza Razavi, Simon R. Arridge, Maxime Sermesant

Proceedings of the Functional Imaging and Modeling of the Heart, 2009

2008

Genetic Programming Approaches for Solving Elliptic Partial Differential Equations.

Andras Sobester, Prasanth B. Nair, Andy J. Keane

IEEE Trans. Evol. Comput., 2008

Predictive Haemodynamics in a One-Dimensional Human Carotid Artery Bifurcation. Part II: Application to Graft Design.

Vijaya B. Kolachalama, Neil W. Bressloff, Prasanth B. Nair, Clifford P. Shearman

IEEE Trans. Biomed. Eng., 2008

Hybrid evolutionary algorithm with Hermite radial basis function interpolants for computationally expensive adjoint solvers.

Yew-Soon Ong, Kai Yew Lum, Prasanth B. Nair

Comput. Optim. Appl., 2008

2007

Combining Global and Local Surrogate Models to Accelerate Evolutionary Optimization.

Zongzhao Zhou, Yew-Soon Ong, Prasanth B. Nair, Andy J. Keane, Kai Yew Lum

IEEE Trans. Syst. Man Cybern. Part C, 2007

Predictive Haemodynamics in a One-Dimensional Human Carotid Artery Bifurcation. Part I: Application to Stent Design.

Vijaya B. Kolachalama, Neil W. Bressloff, Prasanth B. Nair, Clifford P. Shearman

IEEE Trans. Biomed. Eng., 2007

Pointwise uniformly convergent numerical treatment for the non-stationary Burger-Huxley equation using grid equidistribution.

Phani Chinchapatnam, Kamal Djidjeli, Prasanth B. Nair

Int. J. Comput. Math., 2007

2006

Max-min surrogate-assisted evolutionary algorithm for robust design.

Yew-Soon Ong, Prasanth B. Nair, Kai Yew Lum

IEEE Trans. Evol. Comput., 2006

Constructing a speculative kernel machine for pattern classification.

Arindam Choudhury, Prasanth B. Nair, Andy J. Keane

Neural Networks, 2006

2004

Hierarchical surrogate-assisted evolutionary optimization framework.

Zongzhao Zhou, Yew-Soon Ong, Prasanth B. Nair

Proceedings of the IEEE Congress on Evolutionary Computation, 2004

2003

Global convergence of unconstrained and bound constrained surrogate-assisted evolutionary search in aerodynamic shape design.

Yew-Soon Ong, Kai Yew Lum, Prasanth B. Nair, Daming Shi, Z. K. Zhang

Proceedings of the IEEE Congress on Evolutionary Computation, 2003

2002

Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels.

Prasanth B. Nair, Arindam Choudhury, Andy J. Keane

J. Mach. Learn. Res., 2002

A Data Parallel Approach for Large-Scale Gaussian Process Modeling.

Arindam Choudhury, Prasanth B. Nair, Andy J. Keane

Proceedings of the Second SIAM International Conference on Data Mining, 2002

2001

Some Greedy Algorithms for Sparse Nonlinear Regression.

Prasanth B. Nair, Arindam Choudhury, Andy J. Keane

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

1999

Metamodeling Techniques For Evolutionary Optimization of Computationally Expensive Problems: Promises and Limitations.

Mohammed El-Beltagy, Prasanth B. Nair, Andy J. Keane

Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), 1999