BMCS E4575
High-dimensional statistics for biomedical data
Statistical machine learning techniques and advanced mathematical concepts for analysis of high-dimensional biomedical data. Topics include optimal transport and probabilistic modeling for multi-modal genomic and imaging data integration and analysis of spatial and temporal dynamics. Programming assignments, problem sets, and a final project will be required.
Topics
- optimal transport and probabilistic modeling for multi-modal genomic and imaging data integration and analysis of spatial and temporal dynamics
Topics explicitly listed in official catalogue description
Prerequisites & course information
Prerequisites: ( APMA E2000 and COMS W4771 and MATH UN2010 ) or ( APMA E2101 ) Strong background in Python (or R) programming- Background in probability/statistics is recommended.
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- High-dimensional statistics for biomedical data · 3.00 points · University catalogue