Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Hoffmann Nico"'
Publikováno v:
Current Directions in Biomedical Engineering, Vol 2, Iss 1, Pp 475-478 (2016)
Intraoperative thermal neuroimaging is a novel intraoperative imaging technique for the characterization of perfusion disorders, neural activity and other pathological changes of the brain. It bases on the correlation of (sub-)cortical metabolism and
Externí odkaz:
https://doaj.org/article/27f14ceb686c4d119089e629251978e8
Autor:
Ramanaik, Chethan Krishnamurthy, Cardona, Juan-Esteban Suarez, Willmann, Anna, Hanfeld, Pia, Hoffmann, Nico, Hecht, Michael
We formulate a data independent latent space regularisation constraint for general unsupervised autoencoders. The regularisation rests on sampling the autoencoder Jacobian in Legendre nodes, being the centre of the Gauss-Legendre quadrature. Revisiti
Externí odkaz:
http://arxiv.org/abs/2309.08228
Autor:
Weber, Dieter, Ehrig, Simeon, Schropp, Andreas, Clausen, Alexander, Achilles, Silvio, Hoffmann, Nico, Bussmann, Michael, Dunin-Borkowski, Rafal, Schroer, Christian G.
We demonstrate live-updating ptychographic reconstruction with ePIE, an iterative ptychography method, during ongoing data acquisition. The reconstruction starts with a small subset of the total data, and as the acquisition proceeds the data used for
Externí odkaz:
http://arxiv.org/abs/2308.10674
Autor:
Willmann, Anna, Cabadağ, Jurjen Couperus, Chang, Yen-Yu, Pausch, Richard, Ghaith, Amin, Debus, Alexander, Irman, Arie, Bussmann, Michael, Schramm, Ulrich, Hoffmann, Nico
Publikováno v:
Machine Learning and the Physical Sciences 2022 workshop, NeurIPS
Understanding and control of Laser-driven Free Electron Lasers remain to be difficult problems that require highly intensive experimental and theoretical research. The gap between simulated and experimentally collected data might complicate studies a
Externí odkaz:
http://arxiv.org/abs/2303.00657
Publikováno v:
DLDE Workshop in the 36th Conference on Neural Information Processing Systems (NeurIPS 2022)
Modelling the temperature of Electric Vehicle (EV) batteries is a fundamental task of EV manufacturing. Extreme temperatures in the battery packs can affect their longevity and power output. Although theoretical models exist for describing heat trans
Externí odkaz:
http://arxiv.org/abs/2212.08403
While the interaction of ultra-intense ultra-short laser pulses with near- and overcritical plasmas cannot be directly observed, experimentally accessible quantities (observables) often only indirectly give information about the underlying plasma dyn
Externí odkaz:
http://arxiv.org/abs/2212.05836
Steerable convolutional neural networks (CNNs) provide a general framework for building neural networks equivariant to translations and transformations of an origin-preserving group $G$, such as reflections and rotations. They rely on standard convol
Externí odkaz:
http://arxiv.org/abs/2212.06096
Autor:
Stiller, Patrick, Makdani, Varun, Pöschel, Franz, Pausch, Richard, Debus, Alexander, Bussmann, Michael, Hoffmann, Nico
The upcoming exascale era will provide a new generation of physics simulations. These simulations will have a high spatiotemporal resolution, which will impact the training of machine learning models since storing a high amount of simulation data on
Externí odkaz:
http://arxiv.org/abs/2211.04770
We demonstrate the utility of physics-informed neural networks (PINNs) as solvers for the non-relativistic, time-dependent Schr\"odinger equation. We study the performance and generalisability of PINN solvers on the time evolution of a quantum harmon
Externí odkaz:
http://arxiv.org/abs/2210.12522
Autor:
Zhdanov, Maksim, Randolph, Lisa, Kluge, Thomas, Nakatsutsumi, Motoaki, Gutt, Christian, Ganeva, Marina, Hoffmann, Nico
Grazing-Incidence Small-Angle X-ray Scattering (GISAXS) is a modern imaging technique used in material research to study nanoscale materials. Reconstruction of the parameters of an imaged object imposes an ill-posed inverse problem that is further co
Externí odkaz:
http://arxiv.org/abs/2210.01543