Articles with public access mandates - Khemraj ShuklaLearn more
Not available anywhere: 1
A first-arrival wavelet based rotation strategy for 3D-3C Data: A Case Study from Rock Springs Uplift, Wyoming
K Shukla, P Jaiswal, S Mallick
SEG International Exposition and Annual Meeting, SEG-2015-5930587, 2015
Mandates: US Department of Energy
Available somewhere: 13
Parallel physics-informed neural networks via domain decomposition
K Shukla, AD Jagtap, GE Karniadakis
Journal of Computational Physics 447, 110683, 2021
Mandates: US Department of Energy, US Department of Defense
Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks
K Shukla, PC Di Leoni, J Blackshire, D Sparkman, GE Karniadakis
J Nondestruct Eval 39 (61), 2020
Mandates: US Department of Defense
A physics-informed neural network for quantifying the microstructural properties of polycrystalline nickel using ultrasound data: A promising approach for solving inverse problems
K Shukla, AD Jagtap, JL Blackshire, D Sparkman, GE Karniadakis
IEEE Signal Processing Magazine 39 (1), 68-77, 2021
Mandates: US Department of Energy, US Department of Defense
Learning two-phase microstructure evolution using neural operators and autoencoder architectures
V Oommen, K Shukla, S Goswami, R Dingreville, GE Karniadakis
nature (npj) computational materials 8 (190), 2022
Mandates: US Department of Energy
Deep neural operators as accurate surrogates for shape optimization
K Shukla, V Oommen, A Peyvan, M Penwarden, N Plewacki, L Bravo, ...
Engineering Applications of Artificial Intelligence 129, 107615, 2024
Mandates: US Department of Defense
Scalable algorithms for physics-informed neural and graph networks
K Shukla, M Xu, N Trask, GE Karniadakis
Data-Centric Engineering 3, e24, 2022
Mandates: US Department of Energy, US Department of Defense
Mycrunchgpt: A llm assisted framework for scientific machine learning
V Kumar, L Gleyzer, A Kahana, K Shukla, GE Karniadakis
Journal of Machine Learning for Modeling and Computing 4 (4), 2023
Mandates: US Department of Energy, US Department of Defense
AI-Aristotle: A physics-informed framework for systems biology gray-box identification
N Ahmadi Daryakenari, M De Florio, K Shukla, GE Karniadakis
PLOS Computational Biology 20 (3), e1011916, 2024
Mandates: US Department of Defense, US National Institutes of Health
A weight-adjusted discontinuous Galerkin method for the poroelastic wave equation: Penalty fluxes and micro-heterogeneities
K Shukla, J Chan, MV de Hoop, P Jaiswal
Journal of Computational Physics 403, 109061, 2020
Mandates: US National Science Foundation
A Framework Based on Symbolic Regression Coupled with eXtended Physics-Informed Neural Networks for Gray-Box Learning of Equations of Motion from Data
E Kiyani, K Shukla, GE Karniadakis, M Karttunen
Computer Methods in Applied Mechanics and Engineering, 415 (https://doi.org …, 2023
Mandates: US Department of Energy, Natural Sciences and Engineering Research Council …
Machine learning as a seismic prior velocity model building method for full-waveform inversion: A case study from Colombia
U Iturrarán-Viveros, AM Muñoz-García, O Castillo-Reyes, K Shukla
Pure and Applied Geophysics 178 (2), 423-448, 2021
Mandates: European Commission
A high order discontinuous Galerkin method for the symmetric form of the anisotropic viscoelastic wave equation
K Shukla, J Chan, MV de Hoop
Computers & Mathematics with Applications 99, 113-132, 2021
Mandates: US National Science Foundation
Learning two-phase microstructure evolution using neural operators and autoencoder architectures
G Karniadakis, V Oommen, K Shukla, S Goswami, R Dingreville
Mandates: US Department of Energy
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