Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Manuel Kroiss"'
Autor:
Tom Schaul, David Silver, James Molloy, Junhyuk Oh, Katrina McKinney, Oriol Vinyals, David H. Choi, Junyoung Chung, Tobias Pohlen, Dani Yogatama, Tobias Pfaff, Demis Hassabis, Michael Mathieu, Dan Horgan, Ivo Danihelka, Igor Babuschkin, Dario Wünsch, Tom Le Paine, Yury Sulsky, Wojciech Marian Czarnecki, Rémi Leblond, Ziyu Wang, Andrew Dudzik, Trevor Cai, Chris Apps, Yuhuai Wu, David Budden, Valentin Dalibard, Timo Ewalds, Oliver Smith, John P. Agapiou, Aja Huang, Roman Ring, Petko Georgiev, Max Jaderberg, Koray Kavukcuoglu, Alexander Vezhnevets, Caglar Gulcehre, Manuel Kroiss, Laurent Sifre, Richard E. Powell, Timothy P. Lillicrap
Publikováno v:
Nature. 575:350-354
Many real-world applications require artificial agents to compete and coordinate with other agents in complex environments. As a stepping stone to this goal, the domain of StarCraft has emerged as an important challenge for artificial intelligence re
Autor:
Dirk Loeffler, Konstantinos D. Kokkaliaris, Timm Schroeder, Fabian J. Theis, Florian Buettner, Philipp S. Hoppe, Oliver Hilsenbeck, Felix Buggenthin, Max Endele, Manuel Kroiss, Carsten Marr, Michael Schwarzfischer, Michael Strasser
Publikováno v:
Nature Methods, 14 (4)
Nat. Methods 14, 403–406 (2017)
Nat. Methods 14, 403–406 (2017)
Differentiation alters molecular properties of stem and progenitor cells, leading to changes in their shape and movement characteristics. We present a deep neural network that prospectively predicts lineage choice in differentiating primary hematopoi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::657292c44c719d3d66a128fa5d640e5a
https://hdl.handle.net/20.500.11850/191567
https://hdl.handle.net/20.500.11850/191567
Autor:
Manuel Kroiss
Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. This work is based on experiments focusing on the lineage choice of CMPs, the progenitors of HSCs, which either become MEP or GMP cells. The author
Autor:
Manuel Kroiss
Publikováno v:
Predicting the Lineage Choice of Hematopoietic Stem Cells ISBN: 9783658128784
Artificial Neural Networks (ANNs) are mathematical models for machine learning, that were inspired by the structure of the central nervous system in animals or humans [56,57]. The human brain is still the most powerful information processing unit for
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b472edfa4f77fa44666fecce1c8a702
https://doi.org/10.1007/978-3-658-12879-1_2
https://doi.org/10.1007/978-3-658-12879-1_2
Autor:
Manuel Kroiss
Publikováno v:
Predicting the Lineage Choice of Hematopoietic Stem Cells
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e95952214290e80bec108b3e2bf177c9
https://doi.org/10.1007/978-3-658-12879-1
https://doi.org/10.1007/978-3-658-12879-1
Autor:
Manuel Kroiss
Publikováno v:
Predicting the Lineage Choice of Hematopoietic Stem Cells ISBN: 9783658128784
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d59c2a93d6f59aac77b843d7c4870b42
https://doi.org/10.1007/978-3-658-12879-1_1
https://doi.org/10.1007/978-3-658-12879-1_1
Autor:
Manuel Kroiss
Publikováno v:
Predicting the Lineage Choice of Hematopoietic Stem Cells ISBN: 9783658128784
The time-lapse movies used in this thesis were conducted at the Institut fur Stammzellforschung (ISF, Helmholtz Zentrum Munchen) in the group of Dr. Timm Schroeder.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af02625497e18ed00d26636bd13e544a
https://doi.org/10.1007/978-3-658-12879-1_3
https://doi.org/10.1007/978-3-658-12879-1_3
Autor:
Manuel Kroiss
Publikováno v:
Predicting the Lineage Choice of Hematopoietic Stem Cells ISBN: 9783658128784
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d79ac843e8cb278a3323278502dc3700
https://doi.org/10.1007/978-3-658-12879-1_4
https://doi.org/10.1007/978-3-658-12879-1_4
Publikováno v:
Ann. Appl. Stat. 9, no. 3 (2015), 1706-1707
Publikováno v:
Ann. Appl. Stat. 8, no. 1 (2014), 309-330
RNA-sequencing has revolutionized biomedical research and, in particular, our ability to study gene alternative splicing. The problem has important implications for human health, as alternative splicing may be involved in malfunctions at the cellular
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b77509963dc4f4ea34b94b344966111c