Ameya D. Jagtap
Orcid: 0000-0002-8831-1000
According to our database1,
Ameya D. Jagtap
authored at least 19 papers
between 2018 and 2024.
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Bibliography
2024
CoRR, 2024
2023
A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions.
J. Comput. Phys., November, 2023
Deep smoothness WENO scheme for two-dimensional hyperbolic conservation laws: A deep learning approach for learning smoothness indicators.
CoRR, 2023
2022
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., 2022
SIAM J. Sci. Comput., 2022
J. Comput. Phys., 2022
Deep Kronecker neural networks: A general framework for neural networks with adaptive activation functions.
Neurocomputing, 2022
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology.
CoRR, 2022
How important are activation functions in regression and classification? A survey, performance comparison, and future directions.
CoRR, 2022
Error estimates for physics informed neural networks approximating the Navier-Stokes equations.
CoRR, 2022
Deep learning of inverse water waves problems using multi-fidelity data: Application to Serre-Green-Naghdi equations.
CoRR, 2022
2021
J. Comput. Phys., 2021
Extended Physics-informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition based Deep Learning Framework for Nonlinear Partial Differential Equations.
Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021
2020
Adaptive activation functions accelerate convergence in deep and physics-informed neural networks.
J. Comput. Phys., 2020
<i>L</i><sup>1</sup>-type smoothness indicators based WENO scheme for nonlinear degenerate parabolic equations.
Appl. Math. Comput., 2020
2019
Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks.
CoRR, 2019
2018
Higher order scheme for two-dimensional inhomogeneous sine-Gordon equation with impulsive forcing.
Commun. Nonlinear Sci. Numer. Simul., 2018