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researcher

Vincenzo Lagani

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG1
  • q-bio.QM1
  • stat.ML1
ORCID 0000-0002-6552-6076

identity via Semantic Scholar / OpenAlex

activity
20162025
most citedFeature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets

7 citations · 7 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2025

Interpretable Causal Representation Learning for Biological Data in the Pathway Space

Jesus de la Fuente, Robert Lehmann, Carlos Ruiz-Arenas +8

Predicting the impact of genomic and drug perturbations in cellular function is crucial for understanding gene functions and drug effects, ultimately leading to improved therapies.…

q-bio.QM2023

IHCV: Discovery of Hidden Time-Dependent Control Variables in Non-Linear Dynamical Systems

Juan Munoz, Subash Balsamy, Juan P. Bernal-Tamayo +6

Discovering non-linear dynamical models from data is at the core of science. Recent progress hinges upon sparse regression of observables using extensive libraries of candidate fun…

stat.ML2016★ 7 cited

Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets

Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni +2

The statistically equivalent signature (SES) algorithm is a method for feature selection inspired by the principles of constrained-based learning of Bayesian Networks. Most of the…

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