Prafulla Dhariwal

I’m a research scientist at OpenAI working on generative models and unsupervised learning. Previously, I was an undergrad at MIT studying computers, math and physics. I’m from Pune and currently live in San Francisco. My name sounds like truffle, but with a P.

Publications

Generative Models

Jukebox: A Generative Model for Music

Jukebox: A Generative Model for Music
[Paper] [Code] [Blog] [Talk]
Prafulla Dhariwal*, Heewoo Jun*, Christine Payne*, Jong Wook Kim, Alec Radford, Ilya Sutskever

Glow: Generative Flow with Invertible 1x1 Convolutions
[Paper] [Code] [Blog] [Talk]
Durk P Kingma*, Prafulla Dhariwal*
Neural Information Processing Systems (NeurIPS), 2018

Variational Lossy Autoencoder

Variational Lossy Autoencoder
[Paper]
Xi Chen, Diederik P Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
International Conference on Learning Representations (ICLR), 2017

Unsupervised Learning

Language Models are Few-Shot Learners
[Paper] [Code]
Tom B Brown*, Benjamin Mann*, Nick Ryder*, Melanie Subbiah*, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, Dario Amodei
Neural Information Processing Systems (NeurIPS), 2020

Generative Pretraining from Pixels
[Paper] [Code] [Blog]
Mark Chen, Alec Radford, Rewon Child, Jeff Wu, Heewoo Jun, Prafulla Dhariwal, David Luan, Ilya Sutskever
International Conference on Machine Learning (ICML), 2020

Scaling Laws

Scaling Laws for Autoregressive Generative Modeling

Scaling Laws for Autoregressive Generative Modeling
[Paper]
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, Alec Radford, Aditya Ramesh, Nick Ryder, Daniel M Ziegler, John Schulman, Dario Amodei, Sam McCandlish

Theorem Proving

Gamepad: A Learning Environment for Theorem Proving

Gamepad: A Learning Environment for Theorem Proving
[Paper] [Code]
Daniel Huang*, Prafulla Dhariwal*, Dawn Song, Ilya Sutskever
International Conference on Learning Representations (ICLR), 2019

Reinforcement Learning

Proximal Policy Optimization Algorithms
[Paper] [Code] [Blog]
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov

Parameter Space Noise for Exploration
[Paper] [Code] [Blog] [Talk]
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz
International Conference on Learning Representations (ICLR), 2018

OpenAI Baselines

OpenAI Baselines
[Code]
Prafulla Dhariwal, Christopher Hesse, Oleg Klimov, Alex Nichol, Matthias Plappert, Alec Radford, John Schulman, Szymon Sidor, Yuhuai Wu, Peter Zhokhov

Quantum Complexity

Improved Quantum Query Complexity Bounds for Some Graph Problems

Improved Quantum Query Complexity Bounds for Some Graph Problems
[Paper]
Prafulla Dhariwal*, Vinay Mayar*

Media

GPT-3

Jukebox