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Paris Perdikaris

PPDONet: Deep Operator Networks for Fast Prediction of Steady-State Solutions in Disk-Planet Systems

May 18, 2023
Shunyuan Mao, Ruobing Dong, Lu Lu, Kwang Moo Yi, Sifan Wang, Paris Perdikaris

* 10 pages, 6 figures, 2 tables; ApJL accepted

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Gaussian Process Port-Hamiltonian Systems: Bayesian Learning with Physics Prior

May 15, 2023
Thomas Beckers, Jacob Seidman, Paris Perdikaris, George J. Pappas

* Accepted at the IEEE Conference on Decision and Control 2022

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Random Weight Factorization Improves the Training of Continuous Neural Representations

Oct 05, 2022
Sifan Wang, Hanwen Wang, Jacob H. Seidman, Paris Perdikaris

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* 33 pages, 21 figures, 12 tables

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$Δ$-PINNs: physics-informed neural networks on complex geometries

Sep 08, 2022
Francisco Sahli Costabal, Simone Pezzuto, Paris Perdikaris

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* 15 pages, 8 figures

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Rethinking the Importance of Sampling in Physics-informed Neural Networks

Jul 05, 2022
Arka Daw, Jie Bu, Sifan Wang, Paris Perdikaris, Anuj Karpatne

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* 17 pages, 13 figures, 2 tables

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