Zobrazeno 1 - 10
of 178
pro vyhledávání: '"Bivariate von Mises distribution"'
Publikováno v:
Journal of the American Statistical Association, 2009 Jun 01. 104(486), 586-596.
Externí odkaz:
https://www.jstor.org/stable/40592207
Publikováno v:
Journal of the American Statistical Association, 2009 Dec 01. 104(488), 1728-1728.
Externí odkaz:
https://www.jstor.org/stable/40592396
Publikováno v:
Journal of the American Statistical Association. 104(486):586-596
Interest in predicting protein backbone conformational angles has prompted the development of modeling and inference procedures for bivariate angular distributions. We present a Bayesian approach to density estimation for bivariate angular data that
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d5ff3ef3b102cbb7afb25604f913f77
http://pubs.amstat.org/doi/abs/10.1198/jasa.2009.0024
http://pubs.amstat.org/doi/abs/10.1198/jasa.2009.0024
Autor:
Chakraborty, Saptarshi1 (AUTHOR), Wong, Samuel W. K.2 (AUTHOR) samuel.wong@uwaterloo.ca
Publikováno v:
Statistical Papers. Apr2023, Vol. 64 Issue 2, p643-675. 33p.
Conference
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Autor:
Kurz, Gerhard, Hanebeck, Uwe D.
Publikováno v:
2015 International Conference on Electromagnetics in Advanced Applications (ICEAA); 2015, p309-315, 7p
Akademický článek
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Publikováno v:
Mathematics, Vol 9, Iss 2749, p 2749 (2021)
Mathematics
Volume 9
Issue 21
Mathematics
Volume 9
Issue 21
Proteins are found in all living organisms and constitute a large group of macromolecules with many functions. Proteins achieve their operations by adopting distinct three-dimensional structures encoded within the sequence of the constituent amino ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f365810b6a9227c3c09c72ac46683206
https://doi.org/10.3390/math9212749
https://doi.org/10.3390/math9212749
Autor:
Bressloff, Paul C
Publikováno v:
PLoS Computational Biology
PLoS Computational Biology, Vol 15, Iss 3, p e1006755 (2019)
PLoS Computational Biology, Vol 15, Iss 3, p e1006755 (2019)
We use stochastic neural field theory to analyze the stimulus-dependent tuning of neural variability in ring attractor networks. We apply perturbation methods to show how the neural field equations can be reduced to a pair of stochastic nonlinear pha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8e1e17875403c54eb172e0fc696b7123
https://pubmed.ncbi.nlm.nih.gov/30883546
https://pubmed.ncbi.nlm.nih.gov/30883546
A key challenge in conformer sampling is finding low-energy conformations with a small number of energy evaluations. We recently demonstrated the Bayesian Optimization Algorithm (BOA) is an effective method for finding the lowest energy conformation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4fa9a4aa3f02c28ac23f0a3cb0bf8a37
https://ora.ox.ac.uk/objects/uuid:1fb288b1-9b3e-4381-b8d9-e41f2b22b0c2
https://ora.ox.ac.uk/objects/uuid:1fb288b1-9b3e-4381-b8d9-e41f2b22b0c2
