My work is mostly concerned with applications in astro-particle physics, a field that is characterized by extreme class imbalances, by a domain-specific post-processing of predictions, and by the fact that all training data is simulated while the learned models must be valid in practice. My current focuses are the aggregation of predictions in terms of ordinal quantification (a.k.a. unfolding), learning under class-conditional label noise, and the smart control of simulations through active class selection.
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Lamarr Institute for Machine Learning and Artificial Intelligence
- Dortmund, Germany
- https://lamarr.cs.tu-dortmund.de/team/dr-mirko-bunse/
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CriticalDifferenceDiagrams.jl
CriticalDifferenceDiagrams.jl PublicPlot critical difference diagrams in Julia
Julia 6
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AcsCertificates.jl
AcsCertificates.jl PublicSupplementary material for papers at ECML-PKDD 2021 and IAL 2021
Julia 1
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CherenkovDeconvolution.jl
CherenkovDeconvolution.jl PublicDeconvolution algorithms popular in Cherenkov astronomy
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MetaConfigurations.jl
MetaConfigurations.jl PublicDefine a set of configurations as a single, more abstract and comprehensive meta-configuration.
Julia
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julia-knn-tutorial
julia-knn-tutorial PublicIn this tutorial you will implement a k-NN classifier in the Julia programming language
Jupyter Notebook 1
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