Research ArticleCOMPUTER SCIENCE
A trainable clustering algorithm based on shortest paths from density peaks
- View ORCID ProfileDiego Ulisse Pizzagalli1,2,
- View ORCID ProfileSantiago Fernandez Gonzalez2,*,† and
- View ORCID ProfileRolf Krause1,*,†
- 1Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera italiana, CH6500 Bellinzona, Switzerland.
- 2Institute of Computational Science, Università della Svizzera italiana, CH6900 Lugano, Switzerland.
- ↵*Corresponding author. Email: santiago.gonzalez{at}irb.usi.ch (S.F.G.); rolf.krause{at}usi.ch (R.K.)
↵† Co-last authors.
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Science Advances 30 Oct 2019:
Vol. 5, no. 10, eaax3770
DOI: 10.1126/sciadv.aax3770
Vol. 5, no. 10, eaax3770
DOI: 10.1126/sciadv.aax3770
Diego Ulisse Pizzagalli
1Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera italiana, CH6500 Bellinzona, Switzerland.
2Institute of Computational Science, Università della Svizzera italiana, CH6900 Lugano, Switzerland.
Santiago Fernandez Gonzalez
2Institute of Computational Science, Università della Svizzera italiana, CH6900 Lugano, Switzerland.
Rolf Krause
1Institute for Research in Biomedicine, Faculty of Biomedical Sciences, Università della Svizzera italiana, CH6500 Bellinzona, Switzerland.
