Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Maria Bånkestad

Showing results (1-10 of 3) with videos related to

Pageof 1
Sort By:
RSC Advances|August 23, 2024
Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networksMaria Bånkestad, Kevin M Dorst, Göran Widmalm, et al.
Neuroimage|April 1, 2018
Bayesian uncertainty quantification in linear models for diffusion MRIJens Sjölund, Anders Eklund, Evren Özarslan, et al.
Current Research in Toxicology|September 13, 2023
hERG-toxicity prediction using traditional machine learning and advanced deep learning techniquesErik Ylipää, Swapnil Chavan, Maria Bånkestad, et al.
Pageof 1

Showing results (1-10 of 3) with videos related to

Sort By:
Pageof 1
RSC Advances|August 23, 2024
Carbohydrate NMR chemical shift prediction by GeqShift employing E(3) equivariant graph neural networksMaria Bånkestad, Kevin M Dorst, Göran Widmalm, et al.
Neuroimage|April 1, 2018
Bayesian uncertainty quantification in linear models for diffusion MRIJens Sjölund, Anders Eklund, Evren Özarslan, et al.
Current Research in Toxicology|September 13, 2023
hERG-toxicity prediction using traditional machine learning and advanced deep learning techniquesErik Ylipää, Swapnil Chavan, Maria Bånkestad, et al.
Pageof 1