Geir Olve Storvik

Bilde av Geir Olve Storvik
English version of this page
Telefon +47 22855894
Mobiltelefon 45201667
Rom 818
Brukernavn
Besøksadresse Moltke Moes vei 35 Niels Henrik Abels hus 0851 OSLO
Postadresse Postboks 1053 Blindern 0316 OSLO

Research interests: Data Science and Computational statistics, Bayesian hierarchial modelling, biological applications, Bayesian Machine Learning

 

Emneord: Statistikk, Statistikk og biostatistikk

Publikasjoner

  • Grytten, Ivar; Rand, Knut Dagestad; Nederbragt, Alexander Johan; Storvik, Geir Olve; Glad, Ingrid Kristine & Sandve, Geir Kjetil (2019). Graph Peak Caller: Calling ChIP-seq peaks on graph-based reference genomes. PLoS Computational Biology.  ISSN 1553-734X.  15(2), s 1- 13 . doi: 10.1371/journal.pcbi.1006731
  • Hubin, Aliaksandr; Storvik, Geir Olve; Grini, Paul Eivind & Butenko, Melinka Alonso (2019). Bayesian binomial regression model with a latent Gaussian field for analysis of epigenetic data, In Y Kharin & Peter Filzmoser (ed.),  Proceedings of Computer Data Analysis and Modeling: Stochastics and Data Science 2019.  Belarusian State University Press.  ISBN 978-985-566-811-5.  1.  s 167 - 171
  • Mysterud, Atle; Bleka, Øyvind; Nielsen, Anders; Steinheim, Geir; Yoccoz, Nigel Gilles & Storvik, Geir Olve (2019). Climate and synchrony of lamb body mass, In Jon Olaf Olaussen (ed.),  Contributions in natural resource economics. Festschrift to Anders Skonhoft.  Fagbokforlaget.  ISBN 9788245024715.  9.  s 183 - 197
  • Hubin, Aliaksandr & Storvik, Geir Olve (2018). Mode jumping MCMC for Bayesian variable selection in GLMM. Computational Statistics & Data Analysis.  ISSN 0167-9473.  127, s 281- 297 . doi: 10.1016/j.csda.2018.05.020 Fulltekst i vitenarkiv.
  • Hubin, Aliaksandr; Storvik, Geir Olve & Frommlet, Florian (2018). A Novel Algorithmic Approach to Bayesian Logic Regression. Bayesian Analysis.  ISSN 1936-0975. . doi: 10.1214/18-BA1141 Fulltekst i vitenarkiv. Vis sammendrag

Se alle arbeider i Cristin

  • Storvik, Geir Olve (2020). Neural networks vs generalized linear models.
  • Storvik, Geir Olve (2020). "Preliminaries for Deep Neural Networks: Recapture of Linear Algebra, Gradient Descents and Generalized Linear Models".
  • Hubin, Aliaksandr & Storvik, Geir Olve (2019). Combining Model and Parameter Uncertainty in Bayesian Neural Networks.
  • Hubin, Aliaksandr & Storvik, Geir Olve (2019). Combining Model and Parameter Uncertainty in Bayesian Neural Networks. Vis sammendrag
  • Hubin, Aliaksandr & Storvik, Geir Olve (2019). Combining Model and Parameter Uncertainty in Bayesian Neural Networks.
  • Hubin, Aliaksandr & Storvik, Geir Olve (2019). Combining Model and Parameter Uncertainty in Bayesian Neural Networks. Vis sammendrag
  • Hubin, Aliaksandr & Storvik, Geir Olve (2019). Combining Model and Parameter Uncertainty in Bayesian Neural Networks.
  • Hubin, Aliaksandr; Storvik, Geir Olve; Grini, Paul Eivind & Butenko, Melinka Alonso (2019). Bayesian binomial regression model with a latent Gaussian field for analysis of epigenetic data.
  • Storvik, Geir Olve (2019). Bayesian approaches to neural networks.
  • Storvik, Geir Olve (2019). Bayesian approaches to neural networks.
  • Storvik, Geir Olve (2019). Bayesian approaches to neural networks.
  • Storvik, Geir Olve (2019). Education in Statistics and Data Science at the University of Oslo.
  • Storvik, Geir Olve (2019). Flexible Bayesian Nonlinear Model Configuration.
  • Storvik, Geir Olve (2019). On the use of Bayesian methods in machine learning.
  • Storvik, Geir Olve & Hubin, Aliaksandr (2019). Combining model and parameter uncertainty in Bayesian neural networks.

Se alle arbeider i Cristin

Publisert 13. nov. 2010 14:06 - Sist endret 8. mai 2020 09:53

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