Physics-informed neural networks for high-speed flows Z Mao, AD Jagtap, GE Karniadakis Computer Methods in Applied Mechanics and Engineering 360, 112789, 2020 | 826 | 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 | 654 | 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 | 634 | 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 | 548 | 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 | 261 | 2020 |

Parallel physics-informed neural networks via domain decomposition K Shukla, AD Jagtap, GE Karniadakis Journal of Computational Physics 447, 110683, 2021 | 226 | 2021 |

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 | 160 | 2022 |

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 | 122 | 2022 |

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 | 102 | 2024 |

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 | 84 | 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 | 83 | 2022 |

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 | 70 | 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 | 60 | 2022 |

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 | 47 | 2023 |

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 | 42 | 2023 |

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 | 20 | 2024 |

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 | 17 | 2020 |

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 | 14 | 2018 |

Kinetic theory based multi-level adaptive finite difference WENO schemes for compressible Euler equations AD Jagtap, R Kumar Wave Motion, 2020 | 11 | 2020 |

Revisiting the inhomogeneously driven sine–Gordon equation AD Jagtap, E Saha, JD George, ASV Murthy Wave Motion 73, 76-85, 2017 | 11 | 2017 |