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Ameya D. Jagtap
Ameya D. Jagtap
Assistant Professor, WPI | Brown University | TIFR-CAM | IISc
Verified email at wpi.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
11182020
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
9032020
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
8742020
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
8132020
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
3592020
Parallel physics-informed neural networks via domain decomposition
K Shukla, AD Jagtap, GE Karniadakis
Journal of Computational Physics 447, 110683, 2021
3232021
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
2572022
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
1612022
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
1432024
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
1202023
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
1172022
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
1102022
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
842023
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
822023
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
752022
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
402024
RiemannONets: Interpretable Neural Operators for Riemann Problems
A Peyvan, V Oommen, AD Jagtap, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 426 (116996), 2024
232024
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
192020
Large Language Model-Based Evolutionary Optimizer: Reasoning with elitism
S Brahmachary, SM Joshi, A Panda, K Koneripalli, AK Sagotra, H Patel, ...
Neurocomputing 622 (129272), 2025
182025
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
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Articles 1–20