Prafulla Dhariwal

25 papers A* 7Journal 15Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Improved Techniques for Training Consistency Models. ICLR Yang Song, Prafulla Dhariwal
2023	A*	`conf`	Consistency Models. ICML Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever
2023	J	`jnl`	Consistency Models. CoRR Yang Song, Prafulla Dhariwal, Mark Chen, Ilya Sutskever
2023	J	`jnl`	Improved Techniques for Training Consistency Models. CoRR Yang Song, Prafulla Dhariwal
2022	A*	`conf`	GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. ICML Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
2022	J	`jnl`	Hierarchical Text-Conditional Image Generation with CLIP Latents. CoRR Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, Mark Chen
2022	J	`jnl`	Point-E: A System for Generating 3D Point Clouds from Complex Prompts. CoRR Alex Nichol, Heewoo Jun, Prafulla Dhariwal, Pamela Mishkin, Mark Chen
2021	A*	`conf`	Diffusion Models Beat GANs on Image Synthesis. NeurIPS Prafulla Dhariwal, Alexander Quinn Nichol
2021	J	`jnl`	Diffusion Models Beat GANs on Image Synthesis. CoRR Prafulla Dhariwal, Alex Nichol
2021	J	`jnl`	GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. CoRR Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, Mark Chen
2021	A*	`conf`	Improved Denoising Diffusion Probabilistic Models. ICML Alexander Quinn Nichol, Prafulla Dhariwal
2021	J	`jnl`	Improved Denoising Diffusion Probabilistic Models. CoRR Alex Nichol, Prafulla Dhariwal
2020	J	`jnl`	Jukebox: A Generative Model for Music. CoRR Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong Wook Kim, Alec Radford, Ilya Sutskever
2020	A*	`conf`	Language Models are Few-Shot Learners. NeurIPS 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
2020	J	`jnl`	Language Models are Few-Shot Learners. CoRR 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
2020	J	`jnl`	Scaling Laws for Autoregressive Generative Modeling. CoRR 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
2019	—	`conf`	GamePad: A Learning Environment for Theorem Proving. ICLR (Poster) Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever
2018	J	`jnl`	GamePad: A Learning Environment for Theorem Proving. CoRR Daniel Huang, Prafulla Dhariwal, Dawn Song, Ilya Sutskever
2018	A*	`conf`	Glow: Generative Flow with Invertible 1x1 Convolutions. NeurIPS Diederik P. Kingma, Prafulla Dhariwal
2018	J	`jnl`	Glow: Generative Flow with Invertible 1x1 Convolutions. CoRR Diederik P. Kingma, Prafulla Dhariwal
2018	—	`conf`	Parameter Space Noise for Exploration. ICLR (Poster) Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz
2017	J	`jnl`	Parameter Space Noise for Exploration. CoRR Matthias Plappert, Rein Houthooft, Prafulla Dhariwal, Szymon Sidor, Richard Y. Chen, Xi Chen, Tamim Asfour, Pieter Abbeel, Marcin Andrychowicz
2017	J	`jnl`	Proximal Policy Optimization Algorithms. CoRR John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, Oleg Klimov
2017	—	`conf`	Variational Lossy Autoencoder. ICLR (Poster) Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
2016	J	`jnl`	Variational Lossy Autoencoder. CoRR Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel