Nishant Panda
Nishant Panda
Information Sciences, CCS-3, Los Alamos National Lab
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Cited by
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Discontinuous Galerkin methods for modeling hurricane storm surge
C Dawson, EJ Kubatko, JJ Westerink, C Trahan, C Mirabito, C Michoski, ...
Advances in Water Resources 34 (9), 1165-1176, 2011
Boussinesq–Green–Naghdi rotational water wave theory
Y Zhang, AB Kennedy, N Panda, C Dawson, JJ Westerink
Coastal Engineering 73, 13-27, 2013
Discontinuous Galerkin methods for solving Boussinesq–Green–Naghdi equations in resolving non-linear and dispersive surface water waves
N Panda, C Dawson, Y Zhang, AB Kennedy, JJ Westerink, AS Donahue
Journal of Computational Physics 273, 572-588, 2014
StressNet-Deep learning to predict stress with fracture propagation in brittle materials
Y Wang, D Oyen, W Guo, A Mehta, CB Scott, N Panda, ...
Npj Materials Degradation 5 (1), 6, 2021
Rotational surf zone modeling for O (μ4) Boussinesq–Green–Naghdi systems
Y Zhang, AB Kennedy, AS Donahue, JJ Westerink, N Panda, C Dawson
Ocean Modelling 79, 43-53, 2014
Generating–absorbing sponge layers for phase-resolving wave models
Y Zhang, AB Kennedy, N Panda, C Dawson, JJ Westerink
Coastal Engineering 84, 1-9, 2014
A Boussinesq-scaled, pressure-Poisson water wave model
AS Donahue, Y Zhang, AB Kennedy, JJ Westerink, N Panda, C Dawson
Ocean Modelling 86, 36-57, 2015
A hybridized discontinuous Galerkin method for the nonlinear Korteweg–de Vries equation
A Samii, N Panda, C Michoski, C Dawson
Journal of Scientific Computing 68, 191-212, 2016
Surrogate models for estimating failure in brittle and quasi-brittle materials
MK Mudunuru, N Panda, S Karra, G Srinivasan, VT Chau, E Rougier, ...
Applied Sciences 9 (13), 2706, 2019
Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling
N Panda, D Osthus, G Srinivasan, D O'Malley, V Chau, D Oyen, ...
Journal of Computational Physics 420, 109719, 2020
A probabilistic clustering approach for identifying primary subnetworks of discrete fracture networks with quantified uncertainty
D Osthus, JD Hyman, S Karra, N Panda, G Srinivasan
SIAM/ASA Journal on Uncertainty Quantification 8 (2), 573-600, 2020
What is the gradient of a scalar function of a symmetric matrix?
S Srinivasan, N Panda
Indian Journal of Pure and Applied Mathematics 54 (3), 907-919, 2023
Accelerating high-strain continuum-scale brittle fracture simulations with machine learning
MG Fernández-Godino, N Panda, D O’Malley, K Larkin, A Hunter, ...
Computational Materials Science 186, 109959, 2021
A data-driven non-linear assimilation framework with neural networks
N Panda, MG Fernández-Godino, HC Godinez, C Dawson
Computational Geosciences 25, 233-242, 2021
Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems.
A Mehta, CB Scott, D Oyen, N Panda, G Srinivasan
AAAI Spring Symposium: MLPS, 2020
Estimating failure in brittle materials using graph theory
MK Mudunuru, N Panda, S Karra, G Srinivasan, VT Chau, E Rougier, ...
arXiv preprint arXiv:1807.11537, 2018
New Boussinesq system for nonlinear water waves
Y Zhang, AB Kennedy, J Westerink, N Panda, C Dawson
Coastal Engineering Proceedings, 4-4, 2012
A Ramble Through Probability: How I Learned to Stop Worrying and Love Measure Theory
S Basu, T Butler, D Estep, N Panda
Society for Industrial and Applied Mathematics, 2024
Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks
D Banesh, N Panda, A Biswas, L Van Roekel, D Oyen, N Urban, ...
2021 IEEE International Conference on Big Data (Big Data), 3731-3739, 2021
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra
K Kontolati, N Klein, N Panda, D Oyen
arXiv preprint arXiv:2108.08709, 2021
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