Jay Whang

According to our database, Jay Whang authored at least 12 papers between 2018 and 2023.

Collaborative distances:

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

2023

Model-Based Deep Learning.

Nir Shlezinger, Jay Whang, Yonina C. Eldar, Alexandros G. Dimakis

Proc. IEEE, May, 2023

2022

Imagen Video: High Definition Video Generation with Diffusion Models.

Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans

CoRR, 2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Raphael Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi

CoRR, 2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deblurring via Stochastic Refinement.

Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G. Dimakis, Peyman Milanfar

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Neural Distributed Source Coding.

Jay Whang, Anish Acharya, Hyeji Kim, Alexandros G. Dimakis

CoRR, 2021

Composing Normalizing Flows for Inverse Problems.

Jay Whang, Erik M. Lindgren, Alex Dimakis

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

Solving Inverse Problems with a Flow-based Noise Model.

Jay Whang, Qi Lei, Alex Dimakis

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

2020

Compressed Sensing with Invertible Generative Models and Dependent Noise.

Jay Whang, Qi Lei, Alexandros G. Dimakis

CoRR, 2020

Conditional Sampling from Invertible Generative Models with Applications to Inverse Problems.

Erik M. Lindgren, Jay Whang, Alexandros G. Dimakis

CoRR, 2020

2019

Training Variational Autoencoders with Buffered Stochastic Variational Inference.

Rui Shu, Hung H. Bui, Jay Whang, Stefano Ermon

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Strategic Object Oriented Reinforcement Learning.

Ramtin Keramati, Jay Whang, Patrick Cho, Emma Brunskill

CoRR, 2018