Ben Poole

Ben Poole

I'm a research scientist at Google Brain, where I work on deep generative models and understanding neural networks.

I did my PhD at Stanford University advised by Surya Ganguli in the Neural Dynamics and Computation lab. My thesis was on computational tools to develop a better understanding of both biological and aritficial neural networks. I did my undergrad at Carnegie Mellon University, where I was advised by Tai Sing Lee. I've worked at DeepMind, Google Research, Intel Research Pittsburgh, and the NYU Center for Neural Science.

Check out my website.
Authored Publications
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    Google
Variational Prediction
Alex Alemi
AABI 2023 (2023)
Learning Energy-Based Models by Diffusion Recovery Likelihood
Ruiqi Gao
Yang Song
Ying Nian Wu
Diederik P. Kingma
Proceedings of ICLR'21 (2021)
Score-based generative modeling through stochastic differential equations
Yang Song
Jascha Sohl-dickstein
Diederik P. Kingma
Abhishek Kumar
Stefano Ermon
ICLR 2021 (2021) (to appear)
Variational Diffusion Models
Diederik P. Kingma
Jonathan Ho
Advances in Neural Information Processing Systems 34 (NeurIPS 2021) (2021)
On Implicit Regularization in β-VAE
Abhishek Kumar
Proceedings of the 37th International Conference on Machine Learning (ICML), 2020
On variational bounds of mutual information
Sherjil Ozair
Aäron van den Oord
Alex Alemi
ICML (2019)
Discrete Flows: Invertible Generative Models of Discrete Data
Keyon Vafa
Kumar Krishna Agrawal
Laurent Dinh
NeurIPS (2019)
Unrolled Generative Adversarial Networks
Luke Metz
David Pfau
Jascha Sohl-Dickstein
ICLR (2017)