Michael Penwarden

16 papers A* 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	ArGEnT: Arbitrary Geometry-encoded Transformer for Operator Learning. CoRR Wenqian Chen, Yucheng Fu, Michael Penwarden, Pratanu Roy, Panos Stinis
2025	J	`jnl`	SUPN: Shallow Universal Polynomial Networks. CoRR Zachary Morrow, Michael Penwarden, Brian Chen, Aurya Javeed, Akil Narayan, John D. Jakeman
2024	J	`jnl`	Comment on "Trans-Net: A transferable pretrained neural networks based on temporal domain decomposition for solving partial differential equations" by D. Zhang, Y. Li, and S. Ying. Comput. Phys. Commun. Michael Penwarden
2024	J	`jnl`	Deep neural operators as accurate surrogates for shape optimization. Eng. Appl. Artif. Intell. Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Nicholas Plewacki, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
2024	J	`jnl`	Kolmogorov n-Widths for Multitask Physics-Informed Machine Learning (PIML) Methods: Towards Robust Metrics. CoRR Michael Penwarden, Houman Owhadi, Robert M. Kirby
2024	J	`jnl`	Kolmogorov n-widths for multitask physics-informed machine learning (PIML) methods: Towards robust metrics. Neural Networks Michael Penwarden, Houman Owhadi, Robert M. Kirby
2023	J	`jnl`	A metalearning approach for Physics-Informed Neural Networks (PINNs): Application to parameterized PDEs. J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2023	J	`jnl`	A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. CoRR Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
2023	J	`jnl`	A unified scalable framework for causal sweeping strategies for Physics-Informed Neural Networks (PINNs) and their temporal decompositions. J. Comput. Phys. Michael Penwarden, Ameya D. Jagtap, Shandian Zhe, George Em Karniadakis, Robert M. Kirby
2023	J	`jnl`	Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils. CoRR Khemraj Shukla, Vivek Oommen, Ahmad Peyvan, Michael Penwarden, Luis Bravo, Anindya Ghoshal, Robert M. Kirby, George Em Karniadakis
2023	A*	`conf`	Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. ICML Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Mike Kirby, Shandian Zhe
2023	J	`jnl`	Neural Operator Learning for Ultrasound Tomography Inversion. CoRR Haocheng Dai, Michael Penwarden, Robert M. Kirby, Sarang C. Joshi
2022	J	`jnl`	Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks. CoRR Shibo Li, Michael Penwarden, Robert M. Kirby, Shandian Zhe
2022	J	`jnl`	Multifidelity modeling for Physics-Informed Neural Networks (PINNs). J. Comput. Phys. Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	J	`jnl`	Multifidelity Modeling for Physics-Informed Neural Networks (PINNs). CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
2021	J	`jnl`	Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach. CoRR Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby