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Pablo Samuel Castro

Pablo Samuel Castro has 2 papers in our library, in 2021–2023; often with Aaron Courville, Jordan Terry, Lucas Willems.

2 papers in our library · 2021–2023

OpenAlex · ORCID · h-index 20 · 103 works · 2,055 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 80 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #8069

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

🎓Université de MontréalMontreal · Canada2021–2026 · 19 paperscurrent🔬Mila - Quebec Artificial Intelligence InstituteMontreal · Canada2024–2026 · 14 paperscurrent🏢GoogleMountain View · United States2013–2025 · 31 papers🎓McGill UniversityMontreal · Canada2007–2024 · 10 papers🎓Télécom SudParisÉvry-Courcouronnes · France2012–2015 · 6 papers🔬Centre National de la Recherche ScientifiqueParis · France2012–2015 · 4 papers🔬Institut Mines-TélécomPalaiseau · France2012–2013 · 3 papers🔬Services répartis, Architectures, MOdélisation, Validation, Administration des RéseauxÉvry-Courcouronnes · France2012–2013 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 2The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksComputer Science · 2 works

 Works by year

2020s

20231 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Deep Reinforcement Learning at the Edge of the Statistical Precipice (2021 · 90 citations)
    The authors examine how reliably algorithms are compared in deep RL when only a few runs per task are available.
  2. Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks (2023 · 25 citations)
    Popular RL benchmark suites such as Gym and dm_control mostly test motor control or visual perception. They are poorly suited to studying goal-directed reasoning or instruction following, and adding new objectives to them is hard. The authors present Minigrid, a collection of 2D GridWorld tasks, and Miniworld, a set…

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. Autonomous navigation of stratospheric balloons using reinforcement learning ↗Nature · no summary yetMarc G. Bellemare et al.2020 · 296 citations
  2. Deep Reinforcement Learning at the Edge of the Statistical PrecipicearXiv:2108.13264Rishabh Agarwal, Max Schwarzer, Pablo Samuel Castro, et al.2021 · 90 citations
  3. Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented TasksarXiv:2306.13831Maxime Chevalier-Boisvert, Bolun Dai, Mark Towers, et al.2023 · 25 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 80 times (of the 149,439 papers whose bibliographies we read); 16 citing papers with a page here →.

Updated

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