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Michael Biehl

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Interpretable machine learning in endocrinology, M. Biehl, APPIS 2024
byMichael Biehl
 
ESE-Eyes-2023.pdf
byMichael Biehl
 
APPIS-FDGPET.pdf
byMichael Biehl
 
stat-phys-appis-reduced.pdf
byMichael Biehl
 
prototypes-AMALEA.pdf
byMichael Biehl
 
stat-phys-AMALEA.pdf
byMichael Biehl
 
Evidence for tissue and stage-specific composition of the ribosome: machine learning analysis of ribosomal protein mRNA data
byMichael Biehl
 
The statistical physics of learning revisted: Phase transitions in layered neural networks
byMichael Biehl
 
Interpretable machine-learning (in endocrinology and beyond)
byMichael Biehl
 
Biehl hanze-2021
byMichael Biehl
 
2020: Prototype-based classifiers and relevance learning: medical applications, video: https://www.youtube.com/watch?v=XfWz0s1IQYk
byMichael Biehl
 
2020: Phase transitions in layered neural networks: ReLU vs. sigmoidal activation
byMichael Biehl
 
2020: So you thought the ribosome was constant and conserved ...
byMichael Biehl
 
Prototype-based classifiers and their applications in the life sciences
byMichael Biehl
 
Prototype-based models in machine learning
byMichael Biehl