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Marco Virgolin

Marco Virgolin has 2 papers in our library, in 2021–2022; often with Ying Jin.

2 papers in our library · 2021–2022

OpenAlex · ORCID · Wikidata · h-index 16 · 68 works · 768 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 29 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6848

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🔬Centrum Wiskunde & InformaticaAmsterdam · Netherlands2015–2024 · 34 papersEmployment 2015–2020 · Life Sciences and HealthEmployment 2021–2023 · Scientific Staff Member (tenure track), Life Sciences and Health🎓Chalmers University of TechnologyGothenburg · Sweden2020–2022 · 5 papersEmployment 2020–2021
🏛️IKEAAmsterdam · Netherlands2023–2024Employment 2023–2024 · Senior Data Scientist
🏛️InSilicoTrials Technologies's-Hertogenbosch · Netherlands2024Employment since 2024 · Head of AI
🏛️Chalmers tekniska högskola ABGoteborg · Sweden2020–2021Employment 2020–2021 · Postdoctoral fellow

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksInformation Systems · 1 workComputational Theory and Mathematics · 1 work

 Works by year

2020s

20221 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Contemporary Symbolic Regression Methods and their Relative Performance (2021 · 156 citations)
    Progress in symbolic regression (SR) has been hard to measure because studies rely on small, easy, or outdated test problems.
  2. Symbolic Regression is NP-hard (2022 · 35 citations)
    Symbolic regression (SR) looks for a model of data written as a mathematical formula. The formula is built by composing elements of a primitive set, such as operations, variables and constants. Researchers have long assumed that the task is intractable. Existing methods are either heuristics without optimality…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Contemporary Symbolic Regression Methods and their Relative PerformancearXiv:2107.14351William La Cava, Patryk Orzechowski, Bogdan Burlacu, et al.2021 · 156 citations
  2. Symbolic Regression is NP-hardarXiv:2207.01018Marco Virgolin, Solon P. Pissis2022 · 35 citations
  3. Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search ↗arXiv (Cornell University) · no summary yetPierre-Alexandre Kamienny et al.2023 · 7 citations

 Co-authors here

1 co-author with a page, the most papers together first.

 Cited by

Papers of our library cite their works 29 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

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