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

Michal Valko

Showing results (1-10 of 11) with videos related to

Pageof 2
Sort By:
Studies in Health Technology and Informatics|September 16, 2010
Feature importance analysis for patient management decisionsMichal Valko, Milos Hauskrecht
Proceedings of the ... International Florida AI Research Society Conference. Florida AI Research Symposium|May 21, 2010
Distance Metric Learning for Conditional Anomaly DetectionMichal Valko, Milos Hauskrecht
Journal of Ultrasound|January 16, 2026
Utilizing POCUS in the diagnosis of small bowel obstruction and the barriers to its implementation in resource-limited settings: a systematic reviewAyesha Razakh, Angelina Uzor, April Htoon, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|August 13, 2008
Evidence-based anomaly detection in clinical domainsMilos Hauskrecht, Michal Valko, Branislav Kveton, et al.
Proceedings. IEEE International Conference on Data Mining|October 14, 2014
Conditional Anomaly Detection with Soft Harmonic FunctionsMichal Valko, Branislav Kveton, Hamed Valizadegan, et al.
Proceedings of the ... International Conference on Machine Learning. International Conference on Machine Learning|November 14, 2014
Conditional anomaly detection methods for patient-management alert systemsMichal Valko, Gregory Cooper, Amy Seybert, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|February 25, 2011
Conditional outlier detection for clinical alertingMilos Hauskrecht, Michal Valko, Iyad Batal, et al.
Journal of Biomedical Informatics|September 5, 2012
Outlier detection for patient monitoring and alertingMilos Hauskrecht, Iyad Batal, Michal Valko, et al.
Proceedings of Machine Learning Research|October 9, 2023
Half-Hop: A graph upsampling approach for slowing down message passingMehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, et al.
Advances in Neural Information Processing Systems|December 5, 2022
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural ActivityRan Liu, Mehdi Azabou, Max Dabagia, et al.
Pageof 2

Showing results (1-10 of 11) with videos related to

Sort By:
Pageof 2
Studies in Health Technology and Informatics|September 16, 2010
Feature importance analysis for patient management decisionsMichal Valko, Milos Hauskrecht
Proceedings of the ... International Florida AI Research Society Conference. Florida AI Research Symposium|May 21, 2010
Distance Metric Learning for Conditional Anomaly DetectionMichal Valko, Milos Hauskrecht
Journal of Ultrasound|January 16, 2026
Utilizing POCUS in the diagnosis of small bowel obstruction and the barriers to its implementation in resource-limited settings: a systematic reviewAyesha Razakh, Angelina Uzor, April Htoon, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|August 13, 2008
Evidence-based anomaly detection in clinical domainsMilos Hauskrecht, Michal Valko, Branislav Kveton, et al.
Proceedings. IEEE International Conference on Data Mining|October 14, 2014
Conditional Anomaly Detection with Soft Harmonic FunctionsMichal Valko, Branislav Kveton, Hamed Valizadegan, et al.
Proceedings of the ... International Conference on Machine Learning. International Conference on Machine Learning|November 14, 2014
Conditional anomaly detection methods for patient-management alert systemsMichal Valko, Gregory Cooper, Amy Seybert, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|February 25, 2011
Conditional outlier detection for clinical alertingMilos Hauskrecht, Michal Valko, Iyad Batal, et al.
Journal of Biomedical Informatics|September 5, 2012
Outlier detection for patient monitoring and alertingMilos Hauskrecht, Iyad Batal, Michal Valko, et al.
Proceedings of Machine Learning Research|October 9, 2023
Half-Hop: A graph upsampling approach for slowing down message passingMehdi Azabou, Venkataramana Ganesh, Shantanu Thakoor, et al.
Advances in Neural Information Processing Systems|December 5, 2022
Drop, Swap, and Generate: A Self-Supervised Approach for Generating Neural ActivityRan Liu, Mehdi Azabou, Max Dabagia, et al.
Pageof 2