Marius Zeinhofer - Dokumente zum Namen - alle Infos bei Yasni.de

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arXivhttps://arxiv.org › math[ ] The modelling error in multi-dimensional time-dependent ...

arxiv.org

von R Masri · · Zitiert von: 2 — The modelling error in multi-dimensional time-dependent solute transport models. Authors:Rami Masri, Marius Zeinhofer, Miroslav Kuchta, Marie E.

137.189.49.7

Marius Zeinhofer. Simula Research Laboratory. Abstract. In the first part of the talk, we discuss error estimates for physics-informed neural networks (PINNs).

ACM Digital Library

dl.acm.org

von P Dondl · · Zitiert von: 3 — Author Picture Marius Zeinhofer. View Profile. Authors Info & Claims. SIAM Journal on Applied MathematicsVolume 82Issue 301 January 2022pp

PINN-PAD: Physics Informed Neural Networks in PADova

pinn-pad.dicea.unipd.it

von A Jnini · · Zitiert von: 2 — = uk + dk. 1. Johannes Müller and Marius Zeinhofer. “Achieving High Accuracy with PINNs via. Energy Natural Gradient Descent”. In: ICML (2023) ...

Proceedings of Machine Learning Research

proceedings.mlr.press

von J Müller · · Zitiert von: 12 — Johannes Müller and Marius Zeinhofer. Error Estimates for the Variational Training of Neural. Networks with Boundary Penalty. arXiv preprint arXiv: , ...

Septentrio Academic Publishing

septentrio.uit.no

von L Courte · Zitiert von: 9 — Luca Courte and Marius Zeinhofer. ∗1. 1Simula Research Laboratory. Abstract. We analyze the training process of the Deep Ritz. Method for elliptic equations ...

Universidade de Lisboa

iccb2022.tecnico.ulisboa.pt

von P Dondl · Zitiert von: 2 — -freiburg.de. Keywords: Bone Scaffold Porosity ... [21] Patrick Dondl and Marius Zeinhofer. An efficient model for scaffold ...

SGBNMhttps://sgbnm.de › files › PDFProtokoll

sgbnm.de

— Marius Zeinhofer TriTeam Hochrhein. 00:40, Zwischenstand nach Wettkampf männlich. 1. SSV Offenburg (Badenliga). SSV Offenburg.

Achieving High Accuracy with PINNs via Energy Natural Gradients

arxiv.org

25. Feb · Johannes Müller, Marius Zeinhofer. We propose energy natural gradient descent, a natural gradient method with respect to a Hessian-induced Riemannian metric as an optimization algorithm for physics-informed neural networks (PINNs) and the deep Ritz method.

Achieving High Accuracy for PINNs with Energy Natural Gradients

www.simtech2023.uni-stuttgart.de

Marius Zeinhofer1, Johannes Muller 2 1) Simula Research Laboratory, Oslo, Norway 2) Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany .de We propose energy natural gradient descent, a natural gradient method with respect to a Hessian-induced Riemannian metric as an optimization algorithm

[ ] Variational Formulations of the Strong ...arXiv

arxiv.org

von KA Mardal · — Authors:Kent-Andre Mardal, Jarle Sogn, Marius Zeinhofer. Download a PDF of the paper titled Variational Formulations of the Strong ...

[ ] A Unified Framework for the Error Analysis of Physics ...arxiv.org › math

arxiv.org

· From: Marius Zeinhofer [view email] [v1] Wed, 1 Nov :01:52 UTC (58 KB). Full-text links: Access Paper: Download a PDF of the paper ...

Verwandte Suchanfragen zu Marius Zeinhofer

Patrick Dondl
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Johannes Haubner
Johannes Müller

Johannes Muller
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Dokumente zum Namen Marius Zeinhofer