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Machine Learning & Computational Biology Lab
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Karsten Borgwardt
Karsten Borgwardt
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CV - Karsten Borgwardt
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Research
Research
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Machine Learning
Graph Kernels
Significant Pattern Mining
Nonlinear Measures of Statistical Dependence (Maximum Information Dimension)
Rapid Outlier Detection
Kernel Method for the Two Sample Problem
Confounder-corrected Classification with Support Vector Machines
Significant Pattern Mining (Westfall-Young Light)
Significant Pattern Mining with Covariates (FACS)
Multi-view Spectral Clustering on Conflicting Views
Kernel Conditional Clustering
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Bioinformatics and Computational Biology
Epistasis tools
easyGWAS
LMM-Lasso
SConES
Multi-SConES
Structural Variant Machine (SV-M)
Protein Function Prediction via Graph Kernels
Pathogenicity Prediction
Multi-Locus Mapping of Genetic Heterogeneity (FAIS)
In silico Phenotyping
Genetic Heterogeneity Discovery (FastCMH)
all-GWAS: Virtual Machine
Combinatorial Association Mapping
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Personalized Medicine
Machine Learning for Personalized Medicine
Personalized Swiss Sepsis Study
Machine Learning Frontiers in Precision Medicine
Teaching
Teaching
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Data Mining I
Data Mining II
Student thesis
Previous courses
Tutorials and workshops
Tutorial at ISMB 2018
Workshop at D-BSSE retreat 2019
Publications & Awards
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Publications
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Books
Awards
Krupp Award 2013
PhD theses
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ETH Zurich
D-BSSE
MLCB Lab
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