Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Arne P. Raulf"'
Publikováno v:
Physical Review Research, Vol 6, Iss 3, p 033103 (2024)
We investigate the stationary (late-time) training regime of single- and two-layer underparameterized linear neural networks within the continuum limit of stochastic gradient descent (SGD) for synthetic Gaussian data. In the case of a single-layer ne
Externí odkaz:
https://doaj.org/article/5376911a49544914872f063092a1e3b6
Publikováno v:
Coral Reefs. 40:1713-1728
Polyp bailout is a drastic response to acute stress where coral coloniality breaks down and polyps detach. We induced polyp bailout in Pocillopora acuta with heat stress and tested for differential gene expression using RNAseq and a qPCR assay. Furth
Autor:
Stefanie Noepel-Duennebacke, Aandrea Tannapfel, Jan Stoehlmacher, Hendrik Juette, U. Graeven, Anke Reinacher-Schick, Susanna Hegewisch-Becker, Karsten Schulmann, Rainer Porschen, Dirk Arnold, Arne P. Raulf
Publikováno v:
Journal of Cancer Research and Clinical Oncology
Introduction In a retrospective analysis of two randomized phase III trials in mCRC patients treated first line with oxaliplatin, fluoropyrimidine with and without Bevacizumab (the AIO KRK 0207 and R091 trials) we evaluated the association of high mi
Publikováno v:
ESANN 2021 proceedings.
Autor:
Klaus Gerwert, Arne P. Raulf, Claus Küpper, Lukas Menzen, Axel Mosig, Frederik Großerueschkamp, Joshua Butke
Publikováno v:
Journal of Biophotonics. 14
Infrared spectra obtained from cell or tissue specimen have commonly been observed to involve a significant degree of scattering effects, often Mie scattering, which probably overshadows biochemically relevant spectral information by a nonlinear, non
Deep representation learning for domain adaptatable classification of infrared spectral imaging data
MotivationApplying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56caebca2f08e52c6989110021f19996
https://doi.org/10.1101/584227
https://doi.org/10.1101/584227
Publikováno v:
Bioinformatics (Oxford, England). 36(1)
Motivation Applying infrared microscopy in the context of tissue diagnostics heavily relies on computationally preprocessing the infrared pixel spectra that constitute an infrared microscopic image. Existing approaches involve physical models, which