Prasanth B. Nair

Publication Activity (10 Years)

Years Active: 1999-2023
Publications (10 Years): 14

Top Topics

Gaussian Process

Greedy Algorithms

Top Venues

J. Comput. Phys.

Publications

Kevin Course, Prasanth B. Nair
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs. CoRR (2023)
Kevin Course, Prasanth B. Nair
State estimation of a physical system with unknown governing equations. Nat. 622 (7982) (2023)
Kevin Course, Prasanth B. Nair
Amortized Reparametrization: Efficient and Scalable Variational Inference for Latent SDEs. NeurIPS (2023)
Kevin L. Course, Trefor W. Evans, Prasanth B. Nair
Weak Form Generalized Hamiltonian Learning. CoRR (2021)
Trefor W. Evans, Prasanth B. Nair
Quadruply Stochastic Gaussian Processes. CoRR (2020)
Kevin Course, Trefor W. Evans, Prasanth B. Nair
Weak Form Generalized Hamiltonian Learning. NeurIPS (2020)
Ricardo Baptista, Valentin Stolbunov, Prasanth B. Nair
Some greedy algorithms for sparse polynomial chaos expansions. J. Comput. Phys. 387 (2019)
Trefor W. Evans, Prasanth B. Nair
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF). ICML (2018)
Trefor W. Evans, Prasanth B. Nair
Discretely Relaxing Continuous Variables for tractable Variational Inference. CoRR (2018)
Trefor W. Evans, Prasanth B. Nair
Exploiting Structure for Fast Kernel Learning. CoRR (2018)
Trefor W. Evans, Prasanth B. Nair
Scalable Gaussian Processes with Grid-Structured Eigenfunctions (GP-GRIEF). CoRR (2018)
Trefor W. Evans, Prasanth B. Nair
Exploiting Structure for Fast Kernel Learning. SDM (2018)
Trefor W. Evans, Prasanth B. Nair
Discretely Relaxing Continuous Variables for tractable Variational Inference. NeurIPS (2018)
Valentin Stolbunov, Prasanth B. Nair
Sparse radial basis function approximation with spatially variable shape parameters. Appl. Math. Comput. 330 (2018)
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)
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) (2008)
Andras Sobester, Prasanth B. Nair, Andy J. Keane
Genetic Programming Approaches for Solving Elliptic Partial Differential Equations. IEEE Trans. Evol. Comput. 12 (4) (2008)
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) (2008)
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) (2007)
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) (2007)
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) (2007)
Arindam Choudhury, Prasanth B. Nair, Andy J. Keane
Constructing a speculative kernel machine for pattern classification. Neural Networks 19 (1) (2006)
Yew-Soon Ong, Prasanth B. Nair, Kai Yew Lum
Max-min surrogate-assisted evolutionary algorithm for robust design. IEEE Trans. Evol. Comput. 10 (4) (2006)
Zongzhao Zhou, Yew-Soon Ong, Prasanth B. Nair
Hierarchical surrogate-assisted evolutionary optimization framework. IEEE Congress on Evolutionary Computation (2004)
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)
Arindam Choudhury, Prasanth B. Nair, Andy J. Keane
A Data Parallel Approach for Large-Scale Gaussian Process Modeling. SDM (2002)
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 (2002)
Prasanth B. Nair, Arindam Choudhury, Andy J. Keane
Some Greedy Algorithms for Sparse Nonlinear Regression. ICML (2001)
Mohammed El-Beltagy, Prasanth B. Nair, Andy J. Keane
Metamodeling Techniques For Evolutionary Optimization of Computationally Expensive Problems: Promises and Limitations. GECCO (1999)