Gray Scott

OpenAI

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Scaling Laws for Autoregressive Generative Modeling

Tom Henighan,Jared Kaplan, Mor Katz, Mark Chen, Christopher Hesse, Jacob Jackson, Heewoo Jun,Tom B. Brown, Prafulla Dhariwal,Scott Gray, Chris Hallacy, Benjamin Mann

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Scaling Laws for Neural Language Models

Kaplan Jared,McCandlish Sam,Henighan Tom,Brown Tom B.,Chess Benjamin,Child Rewon,Gray Scott,Radford Alec,Wu Jeffrey, Amodei Dario

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Generating Long Sequences with Sparse Transformers

Rewon Child,Scott Gray,Alec Radford,Ilya Sutskever

arXiv: Learning, (2019)

Cited by150EIBibtex

Dota 2 with Large Scale Deep Reinforcement Learning

Berner Christopher, Brockman Greg, Chan Brooke, Cheung Vicki, Dębiak Przemysław, Dennison Christy, Farhi David, Fischer Quirin, Hashme Shariq, Hesse Chris, Józefowicz Rafal,Gray Scott

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Flexpoint: An Adaptive Numerical Format for Efficient Training of Deep Neural Networks

Urs Koster, Tristan J. Webb,Xin Wang,Marcel Nassar, Arjun K. Bansal, William H. Constable, Oguz H. Elibol,Scott Gray, Stewart Hall, Luke Hornof, Amir Khosrowshahi, Carey Kloss

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), (2017)

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Gpu kernels for block sparse weights

Scott Gray,Alec Radford, Diederik P Kingma

arXiv preprint arXiv:1711.09224, (2017)

Cited by59Bibtex

Fast Algorithms for Convolutional Neural Networks

Andrew Lavin,Scott Gray

CVPR, (2016)

Cited by433EIBibtex

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Papers7 papers

Gray Scott