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Khemraj Shukla
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2020 – today
- 2024
- [j10]Khemraj Shukla
, Vivek Oommen
, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis:
Deep neural operators as accurate surrogates for shape optimization. Eng. Appl. Artif. Intell. 129: 107615 (2024) - [j9]Jesse Chan
, Khemraj Shukla
, Xinhui Wu, Ruofeng Liu, Prani Nalluri:
High order entropy stable schemes for the quasi-one-dimensional shallow water and compressible Euler equations. J. Comput. Phys. 504: 112876 (2024) - [j8]Zheyuan Hu
, Khemraj Shukla
, George Em Karniadakis
, Kenji Kawaguchi:
Tackling the curse of dimensionality with physics-informed neural networks. Neural Networks 176: 106369 (2024) - [j7]Nazanin Ahmadi Daryakenari
, Mario De Florio
, Khemraj Shukla, George Em Karniadakis
:
AI-Aristotle: A physics-informed framework for systems biology gray-box identification. PLoS Comput. Biol. 20(3): 1011916 (2024) - [i18]Khemraj Shukla
, Juan Diego Toscano, Zhicheng Wang, Zongren Zou, George Em Karniadakis:
A comprehensive and FAIR comparison between MLP and KAN representations for differential equations and operator networks. CoRR abs/2406.02917 (2024) - [i17]Khemraj Shukla, Zongren Zou, Chi Hin Chan, Additi Pandey, Zhicheng Wang, George Em Karniadakis:
NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements. CoRR abs/2407.21217 (2024) - 2023
- [j6]Ahmad Peyvan, Khemraj Shukla
, Jesse Chan
, George E. Karniadakis:
High-order methods for hypersonic flows with strong shocks and real chemistry. J. Comput. Phys. 490: 112310 (2023) - [i16]Khemraj Shukla
, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis:
Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils. CoRR abs/2302.00807 (2023) - [i15]Aniruddha Bora
, Khemraj Shukla
, Shixuan Zhang, Bryce Harrop, Ruby Leung, George Em Karniadakis:
Learning bias corrections for climate models using deep neural operators. CoRR abs/2302.03173 (2023) - [i14]Elham Kiyani, Khemraj Shukla, George Em Karniadakis, Mikko Karttunen:
A Framework Based on Symbolic Regression Coupled with eXtended Physics-Informed Neural Networks for Gray-Box Learning of Equations of Motion from Data. CoRR abs/2305.10706 (2023) - [i13]Varun Kumar
, Leonard Gleyzer, Adar Kahana, Khemraj Shukla
, George Em Karniadakis:
CrunchGPT: A chatGPT assisted framework for scientific machine learning. CoRR abs/2306.15551 (2023) - [i12]Elham Kiyani, Mahdi Kooshkbaghi, Khemraj Shukla, Rahul Babu Koneru, Zhen Li, Luis Bravo, Anindya Ghoshal, George Em Karniadakis, Mikko Karttunen:
Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs. CoRR abs/2307.09142 (2023) - [i11]Jesse Chan, Khemraj Shukla
, Xinhui Wu, Ruofeng Liu, Prani Nalluri:
High order entropy stable schemes for the quasi-one-dimensional shallow water and compressible Euler equations. CoRR abs/2307.12089 (2023) - [i10]Zheyuan Hu, Khemraj Shukla
, George Em Karniadakis, Kenji Kawaguchi:
Tackling the Curse of Dimensionality with Physics-Informed Neural Networks. CoRR abs/2307.12306 (2023) - [i9]Nazanin Ahmadi Daryakenari
, Mario De Florio, Khemraj Shukla
, George Em Karniadakis:
AI-Aristotle: A Physics-Informed framework for Systems Biology Gray-Box Identification. CoRR abs/2310.01433 (2023) - [i8]Khemraj Shukla
, Yeonjong Shin:
Randomized Forward Mode of Automatic Differentiation for Optimization Algorithms. CoRR abs/2310.14168 (2023) - [i7]Vivek Oommen, Khemraj Shukla
, Saaketh Desai, Rémi Dingreville, George Em Karniadakis:
Rethinking materials simulations: Blending direct numerical simulations with neural operators. CoRR abs/2312.05410 (2023) - 2022
- [j5]Khemraj Shukla
, Ameya D. Jagtap, James L. Blackshire, Daniel Sparkman, George Em Karniadakis:
A Physics-Informed Neural Network for Quantifying the Microstructural Properties of Polycrystalline Nickel Using Ultrasound Data: A promising approach for solving inverse problems. IEEE Signal Process. Mag. 39(1): 68-77 (2022) - [i6]Vivek Oommen, Khemraj Shukla
, Somdatta Goswami, Rémi Dingreville, George Em Karniadakis:
Learning two-phase microstructure evolution using neural operators and autoencoder architectures. CoRR abs/2204.07230 (2022) - [i5]Khemraj Shukla
, Mengjia Xu, Nathaniel Trask, George Em Karniadakis:
Scalable algorithms for physics-informed neural and graph networks. CoRR abs/2205.08332 (2022) - [i4]Ahmad Peyvan, Khemraj Shukla
, Jesse Chan, George Em Karniadakis:
High-Order Methods for Hypersonic Flows with Strong Shocks and Real Chemistry. CoRR abs/2211.12635 (2022) - 2021
- [j4]Khemraj Shukla
, Jesse Chan
, Maarten V. de Hoop:
A high order discontinuous Galerkin method for the symmetric form of the anisotropic viscoelastic wave equation. Comput. Math. Appl. 99: 113-132 (2021) - [j3]Khemraj Shukla
, Ameya D. Jagtap
, George Em Karniadakis:
Parallel physics-informed neural networks via domain decomposition. J. Comput. Phys. 447: 110683 (2021) - [i3]Khemraj Shukla, Ameya D. Jagtap
, George Em Karniadakis:
Parallel Physics-Informed Neural Networks via Domain Decomposition. CoRR abs/2104.10013 (2021) - 2020
- [j2]Khemraj Shukla
, Jesse Chan
, Maarten V. de Hoop, Priyank Jaiswal
:
A weight-adjusted discontinuous Galerkin method for the poroelastic wave equation: Penalty fluxes and micro-heterogeneities. J. Comput. Phys. 403 (2020) - [i2]Khemraj Shukla, Patricio Clark Di Leoni, James L. Blackshire, Daniel Sparkman, George Em Karniadakis:
Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks. CoRR abs/2005.03596 (2020) - [i1]Khemraj Shukla, Jesse Chan, Maarten V. de Hoop:
A high order discontinuous Galerkin method for the symmetric form of the anisotropic viscoelastic wave equation. CoRR abs/2011.01529 (2020)
2010 – 2019
- 2019
- [j1]Khemraj Shukla
, José M. Carcione
, Reynam da Cruz Pestana, Priyank Jaiswal
, Turgut Özdenvar:
Modeling the wave propagation in viscoacoustic media: An efficient spectral approach in time and space domain. Comput. Geosci. 126: 31-40 (2019)
Coauthor Index
aka: George E. Karniadakis
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last updated on 2024-12-02 22:33 CET by the dblp team
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