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Ameya D. Jagtap
Ameya D. Jagtap
Assistant Professor of Applied Mathematics (Research), Brown University, USA
Verified email at brown.edu - Homepage
Title
Cited by
Cited by
Year
Physics-informed neural networks for high-speed flows
Z Mao, AD Jagtap, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 360, 112789, 2020
8262020
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
6542020
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
6342020
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
5482020
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
2612020
Parallel physics-informed neural networks via domain decomposition
K Shukla, AD Jagtap, GE Karniadakis
Journal of Computational Physics 447, 110683, 2021
2262021
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
1602022
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
1222022
Error estimates for physics informed neural networks approximating the Navier-Stokes equations
TD Ryck, AD Jagtap, S Mishra
IMA Journal of Numerical Analysis 44 (1), 83 -119, 2024
1022024
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
842022
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
832022
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
702023
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
602022
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions
M Penwarden, AD Jagtap, S Zhe, GE Karniadakis, RM Kirby
Journal of Computational Physics 493 (112464), 2023
472023
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology
Z Hu, AD Jagtap, GE Karniadakis, K Kawaguch
Engineering Applications of Artificial Intelligence 126, 107183, 2023
422023
Learning stiff chemical kinetics using extended deep neural operators
S Goswami, AD Jagtap, H Babaee, BT Susi, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 419 (116674), 2024
202024
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
172020
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
142018
Kinetic theory based multi-level adaptive finite difference WENO schemes for compressible Euler equations
AD Jagtap, R Kumar
Wave Motion, 2020
112020
Revisiting the inhomogeneously driven sine–Gordon equation
AD Jagtap, E Saha, JD George, ASV Murthy
Wave Motion 73, 76-85, 2017
112017
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