Zobrazeno 1 - 10
of 6 552
pro vyhledávání: '"P. Buchwald"'
Physical models often contain unknown functions and relations. The goal of our work is to answer the question of how one should excite or control a system under consideration in an appropriate way to be able to reconstruct an unknown nonlinear relati
Externí odkaz:
http://arxiv.org/abs/2405.12153
Autor:
von Buchwald, Theo Juncker, Ziems, Karl Michael, Kjellgren, Erik Rosendahl, Sauer, Stephan P. A., Kongsted, Jacob, Coriani, Sonia
The prediction of spectral properties via linear response (LR) theory is an important tool in quantum chemistry for understanding photo-induced processes in molecular systems. With the advances of quantum computing, we recently adapted this method fo
Externí odkaz:
http://arxiv.org/abs/2404.16586
Snowman is the consensus protocol implemented by the Avalanche blockchain and is part of the Snow family of protocols, first introduced through the original Avalanche leaderless consensus protocol. A major advantage of Snowman is that each consensus
Externí odkaz:
http://arxiv.org/abs/2404.14250
Autor:
Blumenthal, Moritz, Fantinato, Chiara, Unterberg-Buchwald, Christina, Haltmeier, Markus, Wang, Xiaoqing, Uecker, Martin
Purpose: To develop a neural network architecture for improved calibrationless reconstruction of radial data when no ground truth is available for training. Methods: NLINV-Net is a model-based neural network architecture that directly estimates image
Externí odkaz:
http://arxiv.org/abs/2402.06550
Publikováno v:
Scientific Reports 2024;14:3754
In recent years, a variety of deep learning networks for cardiac MRI (CMR) segmentation have been developed and analyzed. However, nearly all of them are focused on cine CMR under breathold. In this work, accuracy of deep learning methods is assessed
Externí odkaz:
http://arxiv.org/abs/2311.14049
In Nuclear Magnetic Resonance (NMR), it is of crucial importance to have an accurate knowledge of the sample probability distribution corresponding to inhomogeneities of the magnetic fields. An accurate identification of the sample distribution requi
Externí odkaz:
http://arxiv.org/abs/2402.12379
This paper is devoted to the development and convergence analysis of greedy reconstruction algorithms based on the strategy presented in [Y. Maday and J. Salomon, Joint Proceedings of the 48th IEEE Conference on Decision and Control and the 28th Chin
Externí odkaz:
http://arxiv.org/abs/2308.15450
Autor:
Paweł Buchwald
Publikováno v:
Safety & Fire Technology, Vol 63, Iss 1, Pp 6-17 (2024)
Aim: The aim of this study is to explore the possibilities of the metaverse environment in the context of simulating the evacuation of people from a building. The research hypothesis assumes the feasibility of applying the metaverse environment to co
Externí odkaz:
https://doaj.org/article/431f1e7111a245f99c22de4dac89191a
Autor:
Dawid Jurczyński, Paweł Buchwald
Publikováno v:
Safety & Fire Technology, Vol 63, Iss 1, Pp 34-43 (2024)
Aim: Exploration and developing mechanisms of advanced data acquisition necessary for training an artificial intelligence model capable of effectively detecting areas with increased susceptibility to fire situations. The study focuses on utilizing da
Externí odkaz:
https://doaj.org/article/7bdd279b5eca4e4f865a5d151d2e9135
Publikováno v:
Health Equity, Vol 8, Iss 1, Pp 307-313 (2024)
Background: Our research team was in the process of recruiting American Indian and Alaska Native (AIAN) women for a community-based intervention to prevent alcohol-exposed pregnancy when the COVID-19 pandemic began. Safety measures adopted at the tri
Externí odkaz:
https://doaj.org/article/4974df4b62fd477ebda57916a863affb