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Michael Bohlke-Schneider
Michael Bohlke-Schneider
Senior Machine Learning Scientist at Amazon
Bestätigte E-Mail-Adresse bei amazon.com
Titel
Zitiert von
Zitiert von
Jahr
Criteria for classifying forecasting methods
T Januschowski, J Gasthaus, Y Wang, D Salinas, V Flunkert, ...
International Journal of Forecasting 36 (1), 167-177, 2020
1062020
GluonTS: Probabilistic and Neural Time Series Modeling in Python.
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
J. Mach. Learn. Res. 21 (116), 1-6, 2020
982020
Neural forecasting: Introduction and literature overview
K Benidis, SS Rangapuram, V Flunkert, B Wang, D Maddix, C Turkmen, ...
arXiv preprint arXiv:2004.10240, 2020
942020
High-dimensional multivariate forecasting with low-rank gaussian copula processes
D Salinas, M Bohlke-Schneider, L Callot, R Medico, J Gasthaus
Advances in neural information processing systems 32, 2019
922019
An integrated workflow for crosslinking mass spectrometry
ML Mendes, L Fischer, ZA Chen, M Barbon, FJ O'Reilly, SH Giese, ...
Molecular systems biology 15 (9), e8994, 2019
892019
Serum albumin domain structures in human blood serum by mass spectrometry and computational biology
A Belsom, M Schneider, L Fischer, O Brock, J Rappsilber
Molecular & Cellular Proteomics 15 (3), 1105-1116, 2016
892016
Protein tertiary structure by crosslinking/mass spectrometry
M Schneider, A Belsom, J Rappsilber
Trends in biochemical sciences 43 (3), 157-169, 2018
812018
X‐ray vs. NMR structures as templates for computational protein design
M Schneider, X Fu, AE Keating
Proteins: Structure, Function, and Bioinformatics 77 (1), 97-110, 2009
642009
Gluonts: Probabilistic time series models in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
arXiv preprint arXiv:1906.05264, 2019
622019
In situ structural restraints from cross-linking mass spectrometry in human mitochondria
PSJ Ryl, M Bohlke-Schneider, S Lenz, L Fischer, L Budzinski, M Stuiver, ...
Journal of proteome research 19 (1), 327-336, 2019
372019
Normalizing kalman filters for multivariate time series analysis
E de Bézenac, SS Rangapuram, K Benidis, M Bohlke-Schneider, R Kurle, ...
Advances in Neural Information Processing Systems 33, 2995-3007, 2020
352020
Combining physicochemical and evolutionary information for protein contact prediction
M Schneider, O Brock
PloS one 9 (10), e108438, 2014
332014
EPSILON-CP: using deep learning to combine information from multiple sources for protein contact prediction
K Stahl, M Schneider, O Brock
BMC bioinformatics 18 (1), 1-11, 2017
322017
Blind testing of cross‐linking/mass spectrometry hybrid methods in CASP11
M Schneider, A Belsom, J Rappsilber, O Brock
Proteins: Structure, Function, and Bioinformatics 84, 152-163, 2016
272016
RBO Aleph: leveraging novel information sources for protein structure prediction
M Mabrouk, I Putz, T Werner, M Schneider, M Neeb, P Bartels, O Brock
Nucleic acids research 43 (W1), W343-W348, 2015
212015
Blind evaluation of hybrid protein structure analysis methods based on cross-linking
A Belsom, M Schneider, O Brock, J Rappsilber
Trends in biochemical sciences 41 (7), 564-567, 2016
192016
The structure of active opsin as a basis for identification of GPCR agonists by dynamic homology modelling and virtual screening assays
M Schneider, S Wolf, J Schlitter, K Gerwert
FEBS letters 585 (22), 3587-3592, 2011
172011
Blind testing cross-linking/mass spectrometry under the auspices of the 11 th critical assessment of methods of protein structure prediction (CASP11)
A Belsom, M Schneider, L Fischer, M Mabrouk, K Stahl, O Brock, ...
Wellcome open research 1, 2016
132016
GluonTS: Probabilistic Time Series Modeling in Python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
arXiv preprint arXiv:1906.05264, 2019
112019
Analysis of free modeling predictions by RBO aleph in CASP 11
M Mabrouk, T Werner, M Schneider, I Putz, O Brock
Proteins: Structure, Function, and Bioinformatics 84, 87-104, 2016
112016
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