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

Antonio Majdandzic

Showing results (1-10 of 6) with videos related to

Pageof 1
Sort By:
Genome Biology|May 10, 2023
Correcting gradient-based interpretations of deep neural networks for genomicsAntonio Majdandzic, Chandana Rajesh, Peter K Koo
Methods in Molecular Biology (Clifton, N.J.)|January 27, 2023
ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural NetworksPeter K Koo, Matt Ploenzke, Praveen Anand, et al.
Plos Computational Biology|May 13, 2021
Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networksPeter K Koo, Antonio Majdandzic, Matthew Ploenzke, et al.
Scientific Reports|September 22, 2015
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random AttacksBoris Podobnik, Tomislav Lipic, Davor Horvatic, et al.
Proceedings of Machine Learning Research|May 19, 2023
Selecting deep neural networks that yield consistent attribution-based interpretations for genomicsAntonio Majdandzic, Chandana Rajesh, Amber Tang, et al.
Nature Communications|March 2, 2016
Multiple tipping points and optimal repairing in interacting networksAntonio Majdandzic, Lidia A Braunstein, Chester Curme, et al.
Pageof 1

Showing results (1-10 of 6) with videos related to

Sort By:
Pageof 1
Genome Biology|May 10, 2023
Correcting gradient-based interpretations of deep neural networks for genomicsAntonio Majdandzic, Chandana Rajesh, Peter K Koo
Methods in Molecular Biology (Clifton, N.J.)|January 27, 2023
ResidualBind: Uncovering Sequence-Structure Preferences of RNA-Binding Proteins with Deep Neural NetworksPeter K Koo, Matt Ploenzke, Praveen Anand, et al.
Plos Computational Biology|May 13, 2021
Global importance analysis: An interpretability method to quantify importance of genomic features in deep neural networksPeter K Koo, Antonio Majdandzic, Matthew Ploenzke, et al.
Scientific Reports|September 22, 2015
Predicting the Lifetime of Dynamic Networks Experiencing Persistent Random AttacksBoris Podobnik, Tomislav Lipic, Davor Horvatic, et al.
Proceedings of Machine Learning Research|May 19, 2023
Selecting deep neural networks that yield consistent attribution-based interpretations for genomicsAntonio Majdandzic, Chandana Rajesh, Amber Tang, et al.
Nature Communications|March 2, 2016
Multiple tipping points and optimal repairing in interacting networksAntonio Majdandzic, Lidia A Braunstein, Chester Curme, et al.
Pageof 1