Zobrazeno 1 - 10 of 60 pro vyhledávání: '"Paris Perdikaris"'
1
Akademický článek
Disk2Planet: A Robust and Automated Machine Learning Tool for Parameter Inference in Disk–Planet Systems
Autor: Shunyuan Mao, Ruobing Dong, Kwang Moo Yi, Lu Lu, Sifan Wang, Paris Perdikaris
Publikováno v: The Astrophysical Journal, Vol 976, Iss 2, p 200 (2024)
We introduce Disk2Planet, a machine-learning-based tool to infer key parameters in disk–planet systems from observed protoplanetary disk structures. Disk2Planet takes as input the disk structures in the form of 2D density and velocity maps, and out
Externí odkaz: https://doaj.org/article/0954bdc246554d74a5185166f6dfcee5
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2
Akademický článek
PPDONet: Deep Operator Networks for Fast Prediction of Steady-state Solutions in Disk–Planet Systems
Autor: Shunyuan Mao, Ruobing Dong, Lu Lu, Kwang Moo Yi, Sifan Wang, Paris Perdikaris
Publikováno v: The Astrophysical Journal Letters, Vol 950, Iss 2, p L12 (2023)
We develop a tool, which we name Protoplanetary Disk Operator Network (PPDONet), that can predict the solution of disk–planet interactions in protoplanetary disks in real time. We base our tool on Deep Operator Networks, a class of neural networks
Externí odkaz: https://doaj.org/article/58394c9e04534ebcb42a2417cd327fd5
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3
Akademický článek
Fast Characterization of Inducible Regions of Atrial Fibrillation Models With Multi-Fidelity Gaussian Process Classification
Autor: Lia Gander, Simone Pezzuto, Ali Gharaviri, Rolf Krause, Paris Perdikaris, Francisco Sahli Costabal
Publikováno v: Frontiers in Physiology, Vol 13 (2022)
Computational models of atrial fibrillation have successfully been used to predict optimal ablation sites. A critical step to assess the effect of an ablation pattern is to pace the model from different, potentially random, locations to determine whe
Externí odkaz: https://doaj.org/article/602d938595bb4c54aafc7f4df5edb3db
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4
Akademický článek
Physics-Informed Neural Networks for Cardiac Activation Mapping
Autor: Francisco Sahli Costabal, Yibo Yang, Paris Perdikaris, Daniel E. Hurtado, Ellen Kuhl
Publikováno v: Frontiers in Physics, Vol 8 (2020)
A critical procedure in diagnosing atrial fibrillation is the creation of electro-anatomic activation maps. Current methods generate these mappings from interpolation using a few sparse data points recorded inside the atria; they neither include prio
Externí odkaz: https://doaj.org/article/f96249a175624e17bd50ccb5ae280d8d
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7
Feasibility of Vascular Parameter Estimation for Assessing Hypertensive Pregnancy Disorders
Autor: Georgios, Kissas, Eileen, Hwuang, Elizabeth W, Thompson, Nadav, Schwartz, John A, Detre, Walter R, Witschey, Paris, Perdikaris
Publikováno v: Journal of Biomechanical Engineering. 144
Hypertensive pregnancy disorders (HPDs), such as pre-eclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Noninvasive imaging, such as ultrasound (US) and magnetic resonance imaging (MRI), is an important tool for predict
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b8fb70afa8a89c904b170e0f2ad86d1
https://doi.org/10.1115/1.4055679
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8
Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems
Autor: Sebastian Kaltenbach, Paris Perdikaris, Phaedon-Stelios Koutsourelakis
Neural Operators offer a powerful, data-driven tool for solving parametric PDEs as they can represent maps between infinite-dimensional function spaces. In this work, we employ physics-informed Neural Operators in the context of high-dimensional, Bay
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d401e51ae9131904a9447931afd2261
http://arxiv.org/abs/2209.02772
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10
Understanding and Mitigating Gradient Flow Pathologies in Physics-Informed Neural Networks
Autor: Yujun Teng, Paris Perdikaris, Sifan Wang
Publikováno v: SIAM Journal on Scientific Computing. 43:A3055-A3081
The widespread use of neural networks across different scientific domains often involves constraining them to satisfy certain symmetries, conservation laws, or other domain knowledge. Such constrai...
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::1026f9a74fe5ed0c6e3c170da0a0b52e
https://doi.org/10.1137/20m1318043
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