---
title: "Who cites Massively Parallel Methods for — 48 citing papers"
description: "48 papers of the Elamur Research library cite «Massively Parallel Methods for Deep Reinforcement Learning», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/nair-2015-massively-parallel-methods-deep-reinforcement/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Massively Parallel Methods for Deep Reinforcement…](https://md.research.elamur.ai/free/en/papers/nair-2015-massively-parallel-methods-deep-reinforcement/) / cited by

# Who cites «Massively Parallel Methods for Deep Reinforcement Learning»

48 papers of our library cite it (of the 149,439 whose bibliographies we read) · 4 with a page here, the most cited first · [← back to «Massively Parallel Methods for Deep Reinforcement Learning»](https://md.research.elamur.ai/free/en/papers/nair-2015-massively-parallel-methods-deep-reinforcement/)

1. [**TensorFlow: A system for large-scale machine learning arXiv:1605.08695**Martin Abadi, Paul Barham, Jianmin Chen, et al.*2016 · 12,711 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-system-large-scale-machine/)
2. [**TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems arXiv:1603.04467**Martín Abadi, Ashish Agarwal, Paul Barham, et al.*2016 · 9,512 citations*](https://md.research.elamur.ai/free/en/papers/abadi-2016-tensorflow-large-scale-machine-learning/)
3. **[Revisiting the Arcade Learning Environment: Evaluation Protocols and Open Problems for General Agents](https://md.research.elamur.ai/free/en/papers/machado-2017-revisiting-arcade-learning-environment-evaluation/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Marlos C. Machado, Marc G. Bellemare, Erik Talvitie, et al.*2017 · 393 citations*
4. **[HyperTree Proof Search for Neural Theorem Proving](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 151 citations*

44 more papers of our library cite it; they have no page here yet.

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