Prafulla Dhariwal

According to our database, Prafulla Dhariwal authored at least 15 papers between 2017 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Improved Techniques for Training Consistency Models.

Yang Song, Prafulla Dhariwal

CoRR, 2023

Consistency Models.

Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever

Proceedings of the International Conference on Machine Learning, 2023

2022

Point-E: A System for Generating 3D Point Clouds from Complex Prompts.

Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, Mark Chen

CoRR, 2022

Hierarchical Text-Conditional Image Generation with CLIP Latents.

Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen

CoRR, 2022

GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen

Proceedings of the International Conference on Machine Learning, 2022

2021

Diffusion Models Beat GANs on Image Synthesis.

Prafulla Dhariwal, Alexander Quinn Nichol

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improved Denoising Diffusion Probabilistic Models.

Alexander Quinn Nichol, Prafulla Dhariwal

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

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, Alec Radford, Aditya Ramesh, Nick Ryder, Daniel M. Ziegler, John Schulman, Dario Amodei, Sam McCandlish

CoRR, 2020

Jukebox: A Generative Model for Music.

Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever

CoRR, 2020

Language Models are Few-Shot Learners.

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

GamePad: A Learning Environment for Theorem Proving.

Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Glow: Generative Flow with Invertible 1x1 Convolutions.

Diederik P. Kingma, Prafulla Dhariwal

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Parameter Space Noise for Exploration.

Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Proximal Policy Optimization Algorithms.

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov

CoRR, 2017

Variational Lossy Autoencoder.

Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel

Proceedings of the 5th International Conference on Learning Representations, 2017