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Estimating the intrinsic dimension of datasets by a minimal neighborhood information
E Facco, M d’Errico, A Rodriguez, A Laio
Scientific reports 7 (1), 12140, 2017
3782017
Automatic topography of high-dimensional data sets by non-parametric density peak clustering
M d’Errico, E Facco, A Laio, A Rodriguez
Information Sciences 560, 476-492, 2021
762021
Computing the free energy without collective variables
A Rodriguez, M d’Errico, E Facco, A Laio
Journal of chemical theory and computation 14 (3), 1206-1215, 2018
722018
Data segmentation based on the local intrinsic dimension
M Allegra, E Facco, F Denti, A Laio, A Mira
Scientific reports 10 (1), 16449, 2020
38*2020
The intrinsic dimension of protein sequence evolution
E Facco, A Pagnani, ET Russo, A Laio
PLoS computational biology 15 (4), e1006767, 2019
332019
Estimating the intrinsic dimension of datasets by a minimal neighborhood information. Sci. Rep. 7, 12140
E Facco, M d’Errico, A Rodriguez, A Laio
72017
Data classification based on the local intrinsic dimension
M Allegra, E Facco, F Denti, A Laio, A Mira
arXiv preprint arXiv:1902.10459, 2019
32019
The intrinsic dimension of biological data landscapes
E Facco
SISSA, 2017
32017
Reconstructing the topography of multidimensional probability landscapes E
M Allegra, M d'Errico, E Facco, A Laio, A Rodriguez
50th Scientific meeting of the Italian Statistical Society, 2018
2018
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