Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Max Schröder"'
Publikováno v:
Bausteine Forschungsdatenmanagement, Iss 2 (2024)
The Research Data Management Organiser (RDMO) supports researchers in the creation of data management plans (DMPs). The open source software has established itself widely across Germany as the standard DMP tool. For its broader adoption, integration
Externí odkaz:
https://doaj.org/article/a02f78e6b7b045b2910d817af668cd2d
Autor:
Beatrix Adam, Lukas C. Bossert, Magdalene Alice Cyra, Matthias Grönewald, Stephan Janosch, Nina Knipprath, Birte Lindstädt, Lioba Schreyer, Florian Strauß, Henning Timm, Monica Valencia-Schneider, Max Schröder, Sergej Zerr, Bert Zulauf
Publikováno v:
Bausteine Forschungsdatenmanagement, Iss 5 (2023)
Immer mehr Forschende integrieren die Nutzung eines elektronischen Laborbuchs (ELN, electronic lab notebook) in ihren Forschungsalltag, um ihre Forschung digital zu dokumentieren. Die Nutzung eines ELN geht mit einer Reihe von Vorteilen einher: Forsc
Externí odkaz:
https://doaj.org/article/e54a716cc22f4011a83a5d503cc99231
Publikováno v:
Journal of Biomedical Semantics, Vol 13, Iss 1, Pp 1-22 (2022)
Abstract Background Electronic Laboratory Notebooks (ELNs) are used to document experiments and investigations in the wet-lab. Protocols in ELNs contain a detailed description of the conducted steps including the necessary information to understand t
Externí odkaz:
https://doaj.org/article/7b9101de10a147cca811526bd846a0c2
Publikováno v:
SN Applied Sciences, Vol 4, Iss 2, Pp 1-17 (2022)
Abstract In this work, we are concerned with neural network guided goal-oriented a posteriori error estimation and adaptivity using the dual weighted residual method. The primal problem is solved using classical Galerkin finite elements. The adjoint
Externí odkaz:
https://doaj.org/article/048e628aea7f403d8b91570697ccec98
Autor:
Ina Gasterstädt, Max Schröder, Lukas Cronin, Julian Kusch, Lisa-Marie Rennau, Brix Mücher, Stefan Herlitze, Alexander Jack, Petra Wahle
Publikováno v:
Frontiers in Cellular Neuroscience, Vol 16 (2022)
Electrical activity is considered a key driver for the neurochemical and morphological maturation of neurons and the formation of neuronal networks. Designer receptors exclusively activated by designer drugs (DREADDs) are tools for controlling neuron
Externí odkaz:
https://doaj.org/article/3079662117524590922aae64e85c838f
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 7, p e1008023 (2020)
In this study, we propose a new open-source simulation platform that comprises computer-aided design and computer-aided engineering tools for highly automated evaluation of electric field distribution and neural activation during Deep Brain Stimulati
Externí odkaz:
https://doaj.org/article/929d4f5b519b44ff8c9d03307deba9c2
Autor:
Max Schröder
Publikováno v:
Groundings, Vol 8 (2015)
The Gini coefficient, one of the most widely used inequality measures in economics, is thought to report income disparity with a reliable degree of objectivity. However, a critical assessment of the Gini’s implicit normative assumptions reveals tha
Externí odkaz:
https://doaj.org/article/bfd0abb87aad4b6cb9f9c0cc7cfd0db1
Autor:
Kerstin Gierend, Judith A.H. Wodke, Sascha Genehr, Robert Gött, Ron Henkel, Frank Krüger, Markus Mandalka, Lea Michaelis, Alexander Scheuerlein, Max Schröder, Atinkut Zeleke, Dagmar Waltemath
Publikováno v:
Companion Proceedings of the ACM Web Conference 2023.
Publikováno v:
Journal of Artificial Intelligence Research. 63:789-848
Tasks such as social network analysis, human behavior recognition, or modeling biochemical reactions, can be solved elegantly by using the probabilistic inference framework. However, standard probabilistic inference algorithms work at a propositional
The analysis of digital data plays an essential role in today's research investigations. Literate programming techniques interweave documentation and source code in order to provide a comprehensive view on the research process. Jupyter Notebooks are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81e8d4fe0c53c1fdf9d5353cd8aa4910
https://doi.org/10.1016/b978-0-12-801238-3.11686-1
https://doi.org/10.1016/b978-0-12-801238-3.11686-1