| Physics-informed neural networks for high-speed flows Z Mao, AD Jagtap, GE Karniadakis Computer Methods in Applied Mechanics and Engineering 360, 112789, 2020 | 416 | 2020 |
| Adaptive activation functions accelerate convergence in deep and physics-informed neural networks AD Jagtap, K Kawaguchi, GE Karniadakis Journal of Computational Physics 404, 109136, 2020 | 310 | 2020 |
| Conservative physics-informed neural networks on discrete domains for conservation laws: Applications to forward and inverse problems AD Jagtap, E Kharazmi, GE Karniadakis Computer Methods in Applied Mechanics and Engineering 365, 113028, 2020 | 286 | 2020 |
| Extended Physics-Informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition Based Deep Learning Framework for Nonlinear Partial Differential Equations AD Jagtap, GE Karniadakis Communications in Computational Physics 28 (5), 2002-2041, 2020 | 237 | 2020 |
| Locally adaptive activation functions with slope recovery for deep and physics-informed neural networks AD Jagtap, K Kawaguchi, GE Karniadakis Proceedings of the Royal Society A 476 (2239), 20200334, 2020 | 128 | 2020 |
| Parallel physics-informed neural networks via domain decomposition K Shukla, AD Jagtap, GE Karniadakis Journal of Computational Physics 447, 110683, 2021 | 86 | 2021 |
| Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions AD Jagtap, Y Shin, K Kawaguchi, GE Karniadakis Neurocomputing 468, 165-180, 2022 | 45 | 2022 |
| 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, 2022 | 31 | 2022 |
| When Do Extended Physics-Informed Neural Networks (XPINNs) Improve Generalization? Z Hu, AD Jagtap, GE Karniadakis, K Kawaguchi SIAM Journal on Scientific Computing 44 (5), A3158–A3182, 2022 | 30 | 2022 |
| Physics-informed neural networks for inverse problems in supersonic flows AD Jagtap, Z Mao, N Adams, GE Karniadakis Journal of Computational Physics 466, 111402, 2022 | 27 | 2022 |
| Error estimates for physics informed neural networks approximating the Navier-Stokes equations TD Ryck, AD Jagtap, S Mishra IMA Journal of Numerical Analysis, 2023 | 24 | 2023 |
| Deep learning of inverse water waves problems using multi-fidelity data: Application to Serre-Green-Naghdi equations AD Jagtap, D Mitsotakis, GE Karniadakis Ocean Engineering 248, 110775, 2022 | 16 | 2022 |
| Higher Order Scheme for Two-Dimensional Inhomogeneous sine-Gordon Equation with Impulsive Forcing AD Jagtap, ASV Murthy Communications in Nonlinear Science and Numerical Simulation 64, 178-197, 2018 | 11 | 2018 |
| Revisiting the inhomogeneously driven sine–Gordon equation AD Jagtap, E Saha, JD George, ASV Murthy Wave Motion 73, 76-85, 2017 | 8 | 2017 |
| L1 - type smoothness indicators based WENO scheme for nonlinear degenerate parabolic equations S Rathan, R Kumar, AD Jagtap Applied Mathematics and Computation 375, 125112, 2020 | 7 | 2020 |
| Perturbed soliton and director deformation in a ferronematic liquid crystal M Saravanan, AD Jagtap, ASV Murthy Chaos, Solitons & Fractals 106, 220-226, 2018 | 7 | 2018 |
| How important are activation functions in regression and classification? A survey, performance comparison, and future directions AD Jagtap, GE Karniadakis Journal of Machine Learning for Modeling and Computing, 2023 | 6 | 2023 |
| Kinetic theory based multi-level adaptive finite difference WENO schemes for compressible Euler equations AD Jagtap, R Kumar Wave Motion, 2020 | 6 | 2020 |
| On spatio-temporal dynamics of sine-Gordon soliton in nonlinear non-homogeneous media using fully implicit spectral element scheme AD Jagtap Applicable Analysis 100 (1), 37-60, 2021 | 3 | 2021 |
| Higher order spectral element scheme for two-and three-dimensional Cahn–Hilliard equation AD Jagtap, ASV Murthy International Journal of Advances in Engineering Sciences and Applied …, 2018 | 3 | 2018 |
George Em KarniadakisThe Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics and EngineeringΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα brown.edu
