Alex Nichol

According to our database, Alex Nichol authored at least 10 papers between 2018 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

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

Evaluating Large Language Models Trained on Code.

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harrison 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

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

VQ-DRAW: A Sequential Discrete VAE.

Alex Nichol

CoRR, 2020

2018

Gotta Learn Fast: A New Benchmark for Generalization in RL.

Alex Nichol, Vicki Pfau, Christopher Hesse, Oleg Klimov, John Schulman

CoRR, 2018

On First-Order Meta-Learning Algorithms.

Alex Nichol, Joshua Achiam, John Schulman

CoRR, 2018