Nicolò Ruggeri - Google Scholar

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Citations	16	16
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20202021202220232 3 10 1

Co-authors

Fanny YangETH ZurichVerified email at inf.ethz.ch
Konstantin DonhauserETH ZuerichVerified email at ai.ethz.ch
Stefan StojanovicKTHVerified email at kth.se
Federico BattistonAssociate Professor, Department of Network and Data Science, Central European UniversityVerified email at ceu.edu
Armeen TaebUniversity of WashingtonVerified email at uw.edu
Martina ContiscianiMax Planck Institute for Intelligent SystemsVerified email at tuebingen.mpg.de

Nicolò Ruggeri

Nicolò Ruggeri

Max Planck Institute for Intelligent Systems, ETH Zurich

Verified email at tuebingen.mpg.de

Machine Learning Probabilistic Modelling Network Science


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fast rates for noisy interpolation require rethinking the effect of inductive bias K Donhauser, N Ruggeri, S Stojanovic, F Yang International Conference on Machine Learning, 5397-5428, 2022	9	2022
Sampling on networks: estimating eigenvector centrality on incomplete networks N Ruggeri, CD Bacco International Conference on Complex Networks and Their Applications, 90-101, 2019	5	2019
A Principled, Flexible and Efficient Framework for Hypergraph Benchmarking N Ruggeri, F Battiston, C De Bacco arXiv preprint arXiv:2212.08593, 2022	1	2022
Sampling on networks: estimating spectral centrality measures and their impact in evaluating other relevant network measures N Ruggeri, C De Bacco Applied Network Science 5 (1), 1-29, 2020	1	2020
Generalized Inference of Mesoscale Structures in Higher-order Networks N Ruggeri, M Contisciani, F Battiston, C De Bacco arXiv preprint arXiv:2301.11226, 2023		2023
Provable concept learning for interpretable predictions using variational inference A Taeb, N Ruggeri, C Schnuck, F Yang arXiv preprint arXiv:2204.00492, 2022		2022

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Articles 1–6