Heewoo Jun

According to our database, Heewoo Jun authored at least 15 papers between 2017 and 2023.

Collaborative distances:

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

2023

Shap-E: Generating Conditional 3D Implicit Functions.

Heewoo Jun, Alex Nichol

CoRR, 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

Efficient Training of Language Models to Fill in the Middle.

Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, John Schulman, Christine McLeavey, Jerry Tworek, Mark Chen

CoRR, 2022

2021

Training Verifiers to Solve Math Word Problems.

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman

CoRR, 2021

Evaluating Large Language Models Trained on Code.

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, Wojciech Zaremba

CoRR, 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

Distribution Augmentation for Generative Modeling.

Heewoo Jun, Rewon Child, Mark Chen, John Schulman, Aditya Ramesh, Alec Radford, Ilya Sutskever

Proceedings of the 37th International Conference on Machine Learning, 2020

Generative Pretraining From Pixels.

Mark Chen, Alec Radford, Rewon Child, Jeffrey Wu, Heewoo Jun, David Luan, Ilya Sutskever

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Fast Spectrogram Inversion Using Multi-Head Convolutional Neural Networks.

Sercan Ömer Arik, Heewoo Jun, Gregory Frederick Diamos

IEEE Signal Process. Lett., 2019

Language Modeling at Scale.

Md. Mostofa Ali Patwary, Milind Chabbi, Heewoo Jun, Jiaji Huang, Greg Diamos, Kenneth Church

Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

2018

Cold Fusion: Training Seq2Seq Models Together with Language Models.

Anuroop Sriram, Heewoo Jun, Sanjeev Satheesh, Adam Coates

Proceedings of the 19th Annual Conference of the International Speech Communication Association, 2018

Robust Speech Recognition Using Generative Adversarial Networks.

Anuroop Sriram, Heewoo Jun, Yashesh Gaur, Sanjeev Satheesh

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018

2017

Deep Learning Scaling is Predictable, Empirically.

Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory F. Diamos, Heewoo Jun, Hassan Kianinejad, Md. Mostofa Ali Patwary, Yang Yang, Yanqi Zhou

CoRR, 2017

Reducing Bias in Production Speech Models.

Eric Battenberg, Rewon Child, Adam Coates, Christopher Fougner, Yashesh Gaur, Jiaji Huang, Heewoo Jun, Ajay Kannan, Markus Kliegl, Atul Kumar, Hairong Liu, Vinay Rao, Sanjeev Satheesh, David Seetapun, Anuroop Sriram, Zhenyao Zhu

CoRR, 2017